Статті в журналах: "Chaos optique"

1

LE Berre, Martine, Elisabeth Ressayre, and Andrée Tallet. "Chaos dans des systèmes optiques à réaction retardée." Annales des Télécommunications 42, no. 5-6 (May 1987): 324–27. http://dx.doi.org/10.1007/bf02995250.

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2

Amon, A., P. Suret, S. Bielawski, D. Derozier, J. Zemmouri, M. Lefranc, M. Nizette, and T. Erneux. "Instabilités et chaos dans les oscillateurs paramétriques optiques." Journal de Physique IV (Proceedings) 119 (November 2004): 113–14. http://dx.doi.org/10.1051/jp4:2004119016.

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3

Zhang, Ke, and Xiao Ming Cao. "Inclination Errors Evaluation of Planar Lines with a Chaos Optimization." Applied Mechanics and Materials 37-38 (November 2010): 525–28. http://dx.doi.org/10.4028/www.scientific.net/amm.37-38.525.

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To improve inclination error evaluation of planar lines, chaos optimization is proposed to evaluate the minimum zone error in this paper. The evolutional optimum model and the calculation process are introduced. By using the properties of ergodicity, stochastic property, and “regularity” of chaos, the efficiency of chaos optimization algorithm (COA) is much higher than some stochastic algorithms such as simulated anneal algorithm (SAA) and genetic algorithm (GA) when COA is used to a kind of continuous problems. The chaos optimization algorithm can improve the efficiency of searching in the whole field by gradually shrinking the area of optimization variable. Finally, the control experiment results evaluated by different method such as the Least Square, Simplex search, Powell optimum methods and GA, indicate that the proposed method does provide better accuracy on inclination error evaluation.

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4

Yang, Hai. "Study on Traveling Salesman Problem Based on the Improved Chaos Ant Colony Algorithm." Advanced Materials Research 989-994 (July 2014): 2196–99. http://dx.doi.org/10.4028/www.scientific.net/amr.989-994.2196.

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In this paper an improved chaos ant colony algorithm based on return optimization strategy, elite strategy and intersection removal strategy is proposed. The improved algorithm uses orthogonal method to cluster the target points, then adopt chaos technology to optimize initial solution of the ant colony to improve individual quality and chaos perturbation is utilized to avoid the search being trapped into local optimum solutions. The simulation results show that the improved algorithm has higher efficiency in finding optimal path and it is a novel method to solve traveling salesmen problem.

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5

Ammaruekarat, Paranya, and Phayung Meesad. "Multi-Objective Chaos Memetic Algorithm for DTLZ Problems." Advanced Materials Research 403-408 (November 2011): 3676–81. http://dx.doi.org/10.4028/www.scientific.net/amr.403-408.3676.

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Based on Multi-Objective Memetic Algorithm (MOMA), a novel Multi-Objective Chaos Memetic Algorithm (MOCMA) is proposed . MOCMA is presented to keep population’s diversity, avoid local optimum and improve performance of Multi-Objective Memetic Algorithm. By virtue of the over-spread character of chaos sequence, it is used to generate chromosome to overcome redundancies. At the same time, searching space is enlarged by using sensitivity of chaos initial value. The comparisons of MOCMA with NSGAII in DTLZ problems suggest that MOCMA clearly outperforms in converging towards the true pareto front and finding the spread of solutions.

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6

Ourjoumtsev, A., J. Laurat, R. Tualle-Brouri, and Ph Grangier. "Vers la génération de chats de Schrödinger optiques." Journal de Physique IV (Proceedings) 135, no. 1 (October 2006): 247–48. http://dx.doi.org/10.1051/jp4:2006135075.

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7

Gong, Lihua. "Chaos synchronization based on quadratic optimum regulation and control." Europhysics Letters (EPL) 69, no. 6 (March 2005): 886–92. http://dx.doi.org/10.1209/epl/i2004-10429-5.

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8

Feng, Ping. "Dynamic Path Planning Algorithm Based on Chaos Genetic Vehicle Navigation." Applied Mechanics and Materials 142 (November 2011): 12–15. http://dx.doi.org/10.4028/www.scientific.net/amm.142.12.

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The paper puts forward the dynamic path planning algorithm based on improving chaos genetic algorithm by using genetic algorithms and chaos search algorithm. In the practice of navigation, the algorithm can compute at the best path to meet the needs of the navigation in such a short period of planning time. Furthermore,this algorithm can replan a optimum path of the rest paths after the traffic condition in the sudden.

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9

Xu, Fei, and Ke Wang. "Study and Application of Slope Displacement Time Series Forecast Based on CO-WLSSVM." Advanced Materials Research 594-597 (November 2012): 2932–35. http://dx.doi.org/10.4028/www.scientific.net/amr.594-597.2932.

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A multi-dimension admissible support vector wavelet kernel function is introduced and the model of wavelet least square support vector machine (WLSSVM) is optimized by chaos optimization (CO), which is named as wavelet least squares support vector machine based on chaos optimization (CO-WLSSVM).The optimized model improves the forecasting precision depending multi-dimension interpolation character and sparse change character of the wavelet and quick convergence to the optimum solution of the chaos optimization. The CO-WLSSVM is applied to forecast the displacement of left side bank of slope in first-stage hydroelectric station of Jinping. The result shows that the model possesses higher precision of forecasting.

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10

Ni, Hong Mei, Zhian Yi, and Jin Yue Liu. "A Hybrid Particle Swarm Optimization Algorithm for Dynamic Environments." Advanced Materials Research 926-930 (May 2014): 3338–41. http://dx.doi.org/10.4028/www.scientific.net/amr.926-930.3338.

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Chaos is a non-linear phenomenon that widely exists in the nature. Due to the ease of implementation and its special ability to avoid being trapped in local optima, chaos has been a novel optimization technique and chaos-based searching algorithms have aroused intense interests. Many real world optimization problems are dynamic in which global optimum and local optima change over time. Particle swarm optimization has performed well to find and track optima in static environments. When the particle swarm optimization (PSO) algorithm is used in dynamic multi-objective problems, there exist some problems, such as easily falling into prematurely, having slow convergence rate and so on. To solve above problems, a hybrid PSO algorithm based on chaos algorithm is brought forward. The hybrid PSO algorithm not only has the efficient parallelism but also increases the diversity of population because of the chaos algorithm. The simulation result shows that the new algorithm is prior to traditional PSO algorithm, having stronger adaptability and convergence, solving better the question on moving peaks benchmark.

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11

Fu, Xin, Xianzhong Chen, Qingwen Hou, Zhengpeng Wang, and Yixin Yin. "An Improved Chaos Genetic Algorithm for T-Shaped MIMO Radar Antenna Array Optimization." International Journal of Antennas and Propagation 2014 (2014): 1–6. http://dx.doi.org/10.1155/2014/631820.

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In view of the fact that the traditional genetic algorithm easily falls into local optimum in the late iterations, an improved chaos genetic algorithm employed chaos theory and genetic algorithm is presented to optimize the low side-lobe for T-shaped MIMO radar antenna array. The novel two-dimension Cat chaotic map has been put forward to produce its initial population, improving the diversity of individuals. The improved Tent map is presented for groups of individuals of a generation with chaos disturbance. Improved chaotic genetic algorithm optimization model is established. The algorithm presented in this paper not only improved the search precision, but also avoids effectively the problem of local convergence and prematurity. For MIMO radar, the improved chaos genetic algorithm proposed in this paper obtains lower side-lobe level through optimizing the exciting current amplitude. Simulation results show that the algorithm is feasible and effective. Its performance is superior to the traditional genetic algorithm.

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12

Zhou, Guangyu, Aijia Ouyang, and Yuming Xu. "Chaos Glowworm Swarm Optimization Algorithm Based on Cloud Model for Face Recognition." International Journal of Pattern Recognition and Artificial Intelligence 34, no. 12 (March 25, 2020): 2056009. http://dx.doi.org/10.1142/s0218001420560091.

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To overcome the shortcomings of the basic glowworm swarm optimization (GSO) algorithm, such as low accuracy, slow convergence speed and easy to fall into local minima, chaos algorithm and cloud model algorithm are introduced to optimize the evolution mechanism of GSO, and a chaos GSO algorithm based on cloud model (CMCGSO) is proposed in the paper. The simulation results of benchmark function of global optimization show that the CMCGSO algorithm performs better than the cuckoo search (CS), invasive weed optimization (IWO), hybrid particle swarm optimization (HPSO), and chaos glowworm swarm optimization (CGSO) algorithm, and CMCGSO has the advantages of high accuracy, fast convergence speed and strong robustness to find the global optimum. Finally, the CMCGSO algorithm is used to solve the problem of face recognition, and the results are better than the methods from literatures.

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13

LAU, FRANCIS C. M., and CHI K. TSE. "OPTIMUM CORRELATOR-TYPE RECEIVER DESIGN FOR CSK COMMUNICATION SYSTEMS." International Journal of Bifurcation and Chaos 12, no. 05 (May 2002): 1029–38. http://dx.doi.org/10.1142/s0218127402004863.

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In a chaos-shift-keying (CSK) digital communication system, correlators followed by a comparator are typically used for coherent detection of the signal. Such a detection method, however, does not take the temporal variation of the bit energy into consideration. In this paper, an optimum detection for a binary CSK system is derived, taking into account the temporal variation of the bit energy for minimizing the error rates. Simulations are carried out to compare the performance between the optimum receiver and a typical receiver. The results provide theoretical performance benchmarks of coherent CSK systems for future references.

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14

Nie, Xiaohua, Wei Wang, and Haoyao Nie. "Chaos Quantum-Behaved Cat Swarm Optimization Algorithm and Its Application in the PV MPPT." Computational Intelligence and Neuroscience 2017 (2017): 1–11. http://dx.doi.org/10.1155/2017/1583847.

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Cat Swarm Optimization (CSO) algorithm was put forward in 2006. Despite a faster convergence speed compared with Particle Swarm Optimization (PSO) algorithm, the application of CSO is greatly limited by the drawback of “premature convergence,” that is, the possibility of trapping in local optimum when dealing with nonlinear optimization problem with a large number of local extreme values. In order to surmount the shortcomings of CSO, Chaos Quantum-behaved Cat Swarm Optimization (CQCSO) algorithm is proposed in this paper. Firstly, Quantum-behaved Cat Swarm Optimization (QCSO) algorithm improves the accuracy of the CSO algorithm, because it is easy to fall into the local optimum in the later stage. Chaos Quantum-behaved Cat Swarm Optimization (CQCSO) algorithm is proposed by introducing tent map for jumping out of local optimum in this paper. Secondly, CQCSO has been applied in the simulation of five different test functions, showing higher accuracy and less time consumption than CSO and QCSO. Finally, photovoltaic MPPT model and experimental platform are established and global maximum power point tracking control strategy is achieved by CQCSO algorithm, the effectiveness and efficiency of which have been verified by both simulation and experiment.

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15

Putra, Dedi Fazriansyah, Muhammadar Abdullah Abbas, Nadri Solin, and Norhayati Othman. "Effects of Dietary Caulerpa lentillifera Supplementation On Growth Performance and Survival Rate of Milk Fish, Chanos chanos (Forsskål, 1775)." Elkawnie 7, no. 2 (January 17, 2022): 395. http://dx.doi.org/10.22373/ekw.v7i2.10484.

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Abstract: The study aimed to investigate the dietary supplementation effect of sea grape, Caulerpa lentillifera, on the growth performance and survival rate of milkfish, Chanos chanos (Forsskål, 1775). Two hundred fish weighing in the range of 0.20-0.25 g/ind were randomly distributed into 20 of 25 L tanks. The 0 (control), 10, 20, 30, and 40 g/kg of Caulerpa lentillifera powder was supplemented into four formulated feeds and then fed for 49 days. The result exposed that the administration of Caulerpa lentillifera powder in the diet provided a significant effect on the absolute weight gain, absolute length gain, specific growth rate, and feed efficiency (P<0,05), but there was no significant effect on survival rate (P>0,05). The optimum specific growth rate, absolute weight, absolute length and feed efficiency were found at treatment C (20 g/kg diet) with the values of 1.597±0.137 %/days, 4.47±0.08 g, 2.98±0.77 cm and 69.86±2.72 %, respectively. Regarding this result, the supplementation of sea grape (Caulerpa lentillifera) at a 20 g/kg diet is recommended to obtain the optimum growth of milkfish (Chanos chanos).Abstrak: Penelitian ini bertujuan untuk mengetahui pengaruh suplementasi pakan anggur laut Caulerpa lentillifera terhadap performa pertumbuhan dan kelangsungan hidup ikan bandeng, Chanos chanos (Forsskål, 1775). Dua ratus ikan sampel berbobot berkisar 0.20-0.25 g/ind didistribusikan secara acak ke dalam 20 tangki dengan volume masing-masing 25 L. Tepung anggur laut dengan dosis 0 (kontrol), 10, 20, 30, dan 40 g/kg ditambahkan ke dalam lima formulasi pakan dan diberi makan sebanyak 5% dari biomassa ikan dengan frekuensi 2 kali sehari selama 49 hari. Hasil penelitian menunjukkan bahwa pemberian tepung C. lentillifera dalam ransum memberikan pengaruh nyata terhadap laju pertumbuhan spesifik, bobot mutlak, panjang mutlak dan efisiensi pakan (P<0.05), tetapi tidak berpengaruh nyata terhadap kelangsungan hidup (P>0.05). Laju pertumbuhan spesifik, bobot mutlak, panjang mutlak dan efisiensi pakan yang optimum terdapat pada perlakuan C (diet 20 g/kg) dengan nilai 1.597±0.137 %/hari, 4.47±0.08 g, 2.98± 0.77 cm dan 69.86±2.72%. Berkaitan dengan hasil tersebut, disarankan penambahan suplemen anggur laut (C. lentillifera) pada pakan 20 g/kg memberikan pertumbuhan yang optimum bagi ikan bandeng (Chanos chanos).

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16

Ren, Wei Jian, Yuan Jun Qi, Wei Lv, and Cheng Da Li. "A Kind of New Immune Genetic Algorithm and its Application." Applied Mechanics and Materials 48-49 (February 2011): 25–28. http://dx.doi.org/10.4028/www.scientific.net/amm.48-49.25.

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According to the phenomenon of falling into local optimum during solving large-scale optimization problems and the shortcomings of poor convergence of Immune Genetic Algorithm, a new kind of probability selection method based on the concentration for the genetic operation is presented. Considering the features of chaos optimization method, such like not requiring the solved problems with continuity or differentiability, which is unlike the conventional method, and also with a solving process within a certain range traverse in order to find the global optimal solution, a kind of Chaos Immune Genetic Algorithm based on Logistic map and Hénon map is proposed. Through the application to TSP problem, the results have showed the superior to other algorithms.

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17

Zhang, Xiao Hong, and Hong Mei Ning. "Fuzzy Clustering Color Image Segmentation Algorithm Based on CPSO." Advanced Materials Research 461 (February 2012): 526–31. http://dx.doi.org/10.4028/www.scientific.net/amr.461.526.

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Fuzzy C-mean algorithm (FCM) has been well used in the field of color image segmentation. But it is sensitive to initial clustering center and membership matrix, and likely converges into the local minimum, which causes the quality of image segmentation lower. By use of the properties-ergodicity, randomicity of chaos, a new image segmentation algorithm is proposed, which combines the chaos particle swarm optimization (CPSO) and FCM clustering. Some experimental results are shown that this method not only has the ability to prevent the particles to convergence to local optimum, but also has faster convergence and higher accuracy for segmentation. Using the feature distance instead of Euclidian distance, robustness of this method is enhanced.

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18

Dang, Xiao Chao, Zhan Jun Hao, Yan Li, Zhen Yu Lu, and Qi Gao. "Network traffic forecasting combination model based on wavelet transform and chaos algorithm." International Journal of Wavelets, Multiresolution and Information Processing 12, no. 03 (May 2014): 1450029. http://dx.doi.org/10.1142/s0219691314500295.

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Based on wavelet transform and chaos algorithm, this paper presents a Network Traffic Forecasting Combination Model. The model introduces chaos algorithm for training the BP network and optimizing weights so as to avoid gradient descent algorithm that slowly converges and likely obtains local optimum results. Before forecasting, we first perform wavelet decomposition on the pretreated flow. Then, we utilize the FARIMA model and the improved Elman neural network model to forecast according to approximate components and detailed components, respectively. At last, we use the combination model for the network traffic forecasting. Simulation results confirmed the improved accuracy of the model, and comparing to traditional FARIMA model and wavelet neural network (WNN) model, the model can reduce the deviation.

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19

Eris, Fitria Riany, Aris Munandar, Taufik Hidayat, Kartina AM, Meutia, and Dian Anggraeni. "Karakteristik Produk Uli Khas Suku Badui dengan Penambahan Daging Ikan Bandeng (Chanos chanos)." Jurnal Pengolahan Hasil Perikanan Indonesia 23, no. 3 (December 24, 2020): 479–85. http://dx.doi.org/10.17844/jphpi.v23i3.33003.

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Uli adalah pangan lokal khas suku Baduy dengan bahan baku utama beras ketan. Produk tersebut memiliki kandungan karbohidrat yang tinggi, namun rendah jenis gizi lainnya. Oleh karena itu, peningkatan nilai gizi dilakukan melalui penambahan daging ikan bandeng. Tujuan penelitian ini adalah menentukan perlakuan optimum dan karateristik kimia, fisik, serta organoleptik produk uli khas Baduy yang ditambahkan daging ikan bandeng. Penelitian ini dilaksanakan dalam beberapa tahap yaitu preparasi ikan bandeng, pembuatan uli, dan karakterisasi produk yang meliputi kimia (air, abu, protein, dan lemak), fisik (kekerasan), dan organoleptik (rasa, warna, tekstur, dan aroma) dengan panelis tidak terlatih. Perlakuan yang diberikan adalah konsentrasi daging ikan bandeng dengan tiga taraf yaitu 0%, 10%, 20%, dan 30%. Kadar air produk uli tidak berbeda nyata pada tiap perlakuan, sedangkan nilai kadar abunya berkisar antara 1,32-3,00% dan optimum pada konsentrasi 20%. Kadar protein tertinggi terdapat pada konsentrasi 20% dengan nilai 9,15%, sedangkan lemak paling tinggi pada konsentrasi 20% dan 30%. Nilai kekerasan produk uli mengalami penurunan seiring dengan bertambahnya konsentrasi daging ikan bandeng dengan kisaran 2319,59-4184,85 g. Hasil uji organoleptik menunjukkan bahwa pada parameter rasa, warna, tekstur, dan aroma memiliki nilai yang tidak berpengaruh nyata, artinya penambahan daging ikan bandeng masih disukai. Konsentrasi optimum penambahan daging ikan bandeng pada produk uli adalah 20%.

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20

Abbasi, Mostafa, and Ali Gholami. "Automatic nonhyperbolic velocity analysis by polynomial chaos expansion." GEOPHYSICS 83, no. 6 (November 1, 2018): U79—U88. http://dx.doi.org/10.1190/geo2017-0478.1.

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Seismic velocity analysis is one of the most crucial and, at the same time, the most laborious tasks during seismic data processing. This becomes even more difficult and time-consuming when nonhyperbolicity has to be considered in the velocity analysis. Nonhyperbolic velocity analysis provides very useful information during the processing and interpretation of seismic data. The most common approach for considering anisotropy during velocity analysis is to describe the moveout based on a nonhyperbolic equation. The nonhyperbolic moveout equation in vertically transverse isotropic (VTI) media is defined by two parameters: normal moveout (NMO) velocity [Formula: see text] and anellipticity [Formula: see text] (or horizontal velocity [Formula: see text]). We have developed a new approach based on polynomial chaos (PC) expansion for automating nonhyperbolic velocity analysis of common-midpoint (CMP) data in VTI media. For this purpose, we use the PC expansion to approximate the nonhyperbolic semblance function with a very fast-to-simulate function in terms of [Formula: see text] and [Formula: see text]. Then, using particle swarm optimization, we stochastically look for the optimum NMO and horizontal velocities that provide the maximum semblance. In contrary to common approaches for nonhyperbolic velocity analysis in which the two parameters are estimated iteratively in an alternating fashion, we find [Formula: see text] and [Formula: see text] simultaneously. This approach is tested on various data including a simple convolutional model, an anisotropic benchmark model, and a real data set. In all cases, the new method provided acceptable results. Reflections in the CMP corrected using the optimum velocities are properly flattened, and almost no residual moveout is observed.

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21

Wijayanti, Ima, Romadhon Romadhon, and Laras Rianingsih. "KARAKTERISTIK HIDROLISAT PROTEIN IKAN BANDENG (Chanos chanos Forsk) DENGAN KONSENTRASI ENZIM BROMELIN YANG BERBEDA Caracteristic of Milkfish (Chanos chanos Forsk) Protein Hydrolysate as effect of Different Bromelin Enzyme Concentration." SAINTEK PERIKANAN : Indonesian Journal of Fisheries Science and Technology 11, no. 2 (February 25, 2016): 129. http://dx.doi.org/10.14710/ijfst.11.2.129-133.

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ABSTRAK Ikan Bandeng berpotensi menjadi bahan baku hidrolisat protein ikan karena kandungan protein tinggi dan potensi produksi cukup melimpah. Enzim Bromelin merupakan salah satu enzim protease yang dapat membantu dalam mempercepat reaksi hidrolisa protein. Penelitian ini bertujuan untuk mengetahui pengaruh konsentrasi enzim bromelin terhadap kualitas hidrolisat protein Ikan Bandeng (Chanos chanos Forks) segar. Rancangan percobaan yang digunakan pada penelitian ini adalah rancangan acak lengkap dengan perlakuan konsentrasi enzim yang berbeda (4%, 5% dan 6%). Parameter yang diamati adalah nilai kadar protein, lemak, air, karbohidrat, serat kasar dan rendemen. Konsenterasi enzim bromelin berpengaruh nyata pada nilai kadar protein, lemak, air, abu, serat kasar dan rendemen (P<0,05), tetapi tidak berpengaruh nyata pada kadar karbohidrat (P>0,05). Kondisi optimum untuk menghidrolisis daging Ikan Bandeng menjadi hidrolisat protein adalah konsentrasi enzim bromelin 6% dengan waktu hidrolisis selama 6 jam. Kata kunci: Ikan Bandeng (Chanos chanos), hidrolisat protein ikan, enzim bromelin ABSTRACT Milkfish is potentially become the raw material of fish protein hydrolyzate because of the high protein content and relatively abundant production. Bromelin is a protease enzyme that can help on improving protein hydrolyzate quality. This research aimed to determine the effect of bromelain enzyme concentration on the quality of the protein hydrolyzate of milkfish (Chanos chanos Forsk) fresh. The experimental design used in this study was completely randomized design with different concentrations of the enzyme (4%, 5% and 6%) as a treatment. The parameters measured were the contents of protein, fat, water, carbohydrates, crude fiber and yield. The concentration of enzyme bromelin significant effect on contents of protein, fat, water, ash, crude fiber and yield (P<0,05), but no effect on carbohydrates content (P>0,05). The optimum conditions to hydrolyze the milkfish meat into a protein hydrolyzate used 6% bromelin enzyme at the time of hydrolysis for 6 hours. Keywords: Milkfish (Chanos chanos), fish protein hydrolisate, bromelin enzym

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22

Cheng, Ze, Yi Xin Tang, and Yan Li Liu. "3-D Path Planning for UAV Based on Chaos Particle Swarm Optimization." Applied Mechanics and Materials 232 (November 2012): 625–30. http://dx.doi.org/10.4028/www.scientific.net/amm.232.625.

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An improved chaos particle swarm optimization (CPSO) algorithm is proposed on path planning for unmanned aerial vehicle (UAV) to overcome the inadequacy of particle swarm optimization (PSO) algorithm, which falls into local optimum easily and converges slowly in process with poor precision. Through the in-depth analysis of PSO algorithm, the chaos optimization (CO) algorithm principle is introduced into it based on the traditional update operations on the particles’ velocity and position; as a result, the diversity of particles is increased, the suboptimal search on path planning is avoided and the quickness accompanied with accuracy of convergence is improved. Combined with digital map for modeling the UAV’s flight environment, the 3-D path planning is achieved. As the simulation results demonstrated, this hybrid algorithm is superior to the traditional PSO algorithm on path searching, especially in the 3-D environment.

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23

Xia, Cheng Jun, Yun Zhou, and Hao Yu Huang. "A Chaos Particle Swarm Optimization Algorithm for Optimal Power Flow." Advanced Materials Research 1008-1009 (August 2014): 466–72. http://dx.doi.org/10.4028/www.scientific.net/amr.1008-1009.466.

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The chaos particle swarm optimization algorithm was presented to solving optimal power flow. The proposed OPF considers the total cost of generators as the objective functions. To enhance the performance of algorithm, a premature convergence strategy was proposed. The strategy can be divided into two parts. In the first part, a method is introduced to judge premature convergence, while another part provides an advance method to improve the performance of algorithm with searching the solution in total feasible region. The control strategy used to prevent premature convergence will obtain starting values for initial particle before program iterating, so it can provide bitter probability of detecting global optimum solution. The simulation results on standard IEEE 30-bus system minimizing fuel cost of generator show the effectiveness of the chaos particle swarm optimization algorithm, and can obtain a good solution.

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24

Wang, Liping. "Simulation study of an improved firefly algorithm for solving multi-dimensional complex function optimization." Journal of Physics: Conference Series 2383, no. 1 (December 1, 2022): 012081. http://dx.doi.org/10.1088/1742-6596/2383/1/012081.

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To address the shortcomings of the traditional firefly algorithm in global optimization seeking, such as low solution accuracy, unstable convergence and slow optimization speed, a new evolutionary model of firefly algorithm based on the improved Chebyshev chaos mapping is proposed. Firstly, the population distribution is initialised with the improved Chebyshev chaos mapping to improve the population diversity. Secondly, the non-linear dynamic adaptive inertia weights are introduced to regulate the balance between convergence speed and local optimality seeking ability. Then, the boundary variation strategy is introduced to solve the boundary crossing problem to avoid falling into local optimum and continue to improve the population diversity. Finally, simulation experiments are conducted under six benchmark test functions to compare with the traditional firefly algorithm. The experimental results show that the improved algorithm has higher solution accuracy and faster convergence speed.

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25

Peters-Flynn, S., P. S. Spencer, S. Sivaprakasam, I. Pierce, and K. A. Shore. "Identification of the Optimum Time-Delay for Chaos Synchronization Regimes of Semiconductor Lasers." IEEE Journal of Quantum Electronics 42, no. 4 (April 2006): 427–34. http://dx.doi.org/10.1109/jqe.2006.872312.

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26

Xu, Ying, and Hon Gan Chen. "A Novel Global Artificial Fish Swarm Algorithm with Improved Chaotic Search." Advanced Materials Research 538-541 (June 2012): 2594–97. http://dx.doi.org/10.4028/www.scientific.net/amr.538-541.2594.

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The artificial fish swarm algorithm, it may be trapped in local optimum in the later evolution period and its search accuracy is dependent on step length which is hard to keep balance between rapidity and accuracy. Aimed at the defects of AFSA, a novel global artificial fish swarm algorithm is proposed in this paper, in which normal chaotic search on earlier stage is modified , and a differential evolution with improved chaos search was proposed to lead artificial fish into global optimum value. The experimental results show that the proposed algorithm is not only superior to traditional one but also can make the result greater.

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Lytel, Rick, Shoresh Shafei, and Mark G. Kuzyk. "Optimum topology of quasi-one-dimensional nonlinear optical quantum systems." Journal of Nonlinear Optical Physics & Materials 23, no. 02 (June 2014): 1450025. http://dx.doi.org/10.1142/s0218863514500258.

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In this paper, we determine the optimum topology of quasi-one-dimensional nonlinear optical structures using generalized quantum graph models. Quantum graphs are relational graphs endowed with a metric and a multiparticle Hamiltonian acting on the edges, and have a long application history in aromatic compounds, mesoscopic and artificial materials, and quantum chaos. Quantum graphs have recently emerged as models of quasi-one-dimensional electron motion for simulating quantum-confined nonlinear optical systems. This paper derives the nonlinear optical properties of quantum graphs containing the basic star vertex and compares their responses across topological and geometrical classes. We show that such graphs have exactly the right topological properties to generate energy spectra required to achieve large, intrinsic optical nonlinearities. The graphs have the exquisite geometrical sensitivity required to tune wave function overlap in a way that optimizes the transition moments. We show that this class of graphs consistently produces intrinsic optical nonlinearities near the fundamental limits. We discuss the application of the models to the prediction and development of new nonlinear optical structures.

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28

Jie, Zheng. "A Chaos Particle Swarm Optimization Based on Adaptive Inertia Weight." Key Engineering Materials 474-476 (April 2011): 1458–63. http://dx.doi.org/10.4028/www.scientific.net/kem.474-476.1458.

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In this paper, the chaotic optimization algorithm is embedded in traditional PSO algorithm using randomness and ergodicity of the chaotic characteristic, and random numbers and a inertia weight factor in PSO algorithm is substituted respectively by chaotic variables and an adaptive inertia weight function, so the ACEPSO algorithm is proposed in order to overcome the drawbacks of CPSO algorithm that easily falls into local optimum. With the simulation experiments, the effectiveness of ACEPSO algorithm is verified by optimization tests with the complex multi-dimensional function. The simulation results verify that the ACEPSO algorithm is robust, high precision, and strong global convergence, and is a kind of practical and feasible optimization algorithm.

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29

Bakri, Muhammad, Wa Ode Nurlin, and Fendi Fendi. "Effect of temperature and density on the survival rate of transportation nener milkfish Chanos chanos." Akuatikisle: Jurnal Akuakultur, Pesisir dan Pulau-Pulau Kecil 3, no. 1 (May 12, 2019): 11. http://dx.doi.org/10.29239/j.akuatikisle.3.1.11-16.

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The study aims to determine the optimum temperature, optimum density and optimum temperature and density interactions in milkfish (Chanos chanos) transportation. This research was conducted in 2016, in Kendari City, Southeast Sulawesi Province. This study uses a factorial design, consisting of Temperature and Density Factors. The design of the combination treatment of Temperature (A) namely Temperature 15 oC, A2 Temperature 18 oC, A3 Temperature 21 oC. For Density Factor (B), B1 Density of 600 individuals / container, B2 Density of 800 individuals / container, B3 Density of 1,000 individuals / container. The results of analysis of variance at 95% and 99% confidence level, the treatment in this study had no significant effect, where the F count is smaller than the F table. This shows that the combination of temperature and density tested in this study can be used for energy transportation activities for 14 hours. Based on the percentage of graduation of nener life tested in the transportation, starting from the biggest graduation to the smallest life pass, is a combination of 15 oC temperature treatment and a density of 1000 individuals 95.57%, a combination of 18 oC temperature treatment and a density of 800 individuals 95.04 %, a combination of temperature treatment of 21 oC and density of 1000 individuals 91.70%, combination of temperature treatment of 15 oC and density of 800 individuals 90.04%, combination of temperature treatment of 15 oC and density of 600 individuals 89.89%, combination of temperature treatment of 21 oC and a density of 800 individuals 88.67%, a combination of temperature treatment 18 oC and a density of 1000 individuals 88.07%, a combination of temperature treatment 21 oC and a density of 600 individuals 84.33% and a combination of temperature treatment 18 oC and density of 600 individuals 73.28%.

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Wang, Peng, Zhuo Wang, Lihui Wang, Bo-Hu Li, and Binxiu Wang. "The Existence of Autonomous Chaos in EDM Process." Machines 10, no. 4 (March 31, 2022): 252. http://dx.doi.org/10.3390/machines10040252.

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The dynamical evolution of electrical discharge machining (EDM) has drawn immense research interest. Previous research on mechanism analysis has discussed the deterministic nonlinearity of gap states at pulse-on discharging duration, while describing the pulse-off deionization process separately as a stochastic evolutionary process. In this case, the precise model describing a complete machining process, as well as the optimum performance parameters of EDM, can hardly be determined. The main purpose of this paper is to clarify whether the EDM system can maintain consistency in dynamic characteristics within a discharge interval. A nonlinear self-maintained equivalent model is first established, and two threshold conditions are obtained by the Shilnikov theory. The theoretical results prove that the EDM system could lead to chaos without external excitation. The time series of the deionization process recorded in the EDM experiments are then analyzed to further validate this theoretical conclusion. Qualitative chaotic analyses verify that the autonomous EDM process has chaotic characteristics. Quantitative methods are used to estimate the chaotic feature of the autonomous EDM process. By comparing the quantitative results of the autonomous EDM process with the non-autonomous EDM process, a deduction is further made that the EDM system will evolve towards steady chaos under an autonomous state.

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31

Wang, Liming. "Effects of initial conditions and coupling competition modes on behaviors of coupled non-identical fractional-order bistable oscillators." Canadian Journal of Physics 94, no. 11 (November 2016): 1158–66. http://dx.doi.org/10.1139/cjp-2016-0086.

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The effects of the initial conditions and the coupling competition modes on the dynamic behaviors of coupled non-identical fractional-order bistable oscillators are investigated intensively and the various phenomena are explored. The coupled system can be controlled to form chaos synchronization, chaos anti-phase synchronization, amplitude death, oscillation death, etc., by setting the initial conditions or selecting the coupling competition modes. Depending on whether the arbitrary initial conditions can let two coupled oscillators stop oscillating, the dynamic behaviors of the coupled system are further classified into three types, that is, both of oscillators stop oscillating, only one oscillator stops oscillating, and none of oscillators stop oscillating. Based on the principle of Monte Carlo method, the percentages of three types of dynamic behaviors are calculated for the different coupling competition modes and the dynamic behaviors of the coupled system are characterized from the perspective of statistics. Moreover, the mechanism behind the various phenomena is explained in detail by the concept of boundary layer and the optimum coupling competition modes are found.

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Zheng, Yuanzhou, Lei Li, Long Qian, Bosheng Cheng, Wenbo Hou, and Yuan Zhuang. "Sine-SSA-BP Ship Trajectory Prediction Based on Chaotic Mapping Improved Sparrow Search Algorithm." Sensors 23, no. 2 (January 8, 2023): 704. http://dx.doi.org/10.3390/s23020704.

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Objective: In this paper, we propose a Sine chaos mapping-based improved sparrow search algorithm (SSA) to optimize the BP neural network for trajectory prediction of inland river vessels because of the problems of poor accuracy and easy trapping in local optimum in BP neural networks. Method: First, a standard BP model is constructed based on the AIS data of ships in the Yangtze River section. A Sine-BP model is built using Sine chaos mapping to assign neural network weights and thresholds. Finally, a Sine-SSA-BP model is built using the sparrow search algorithm (SSA) to solve the optimal solutions of the neural network weights and thresholds. Result: The Sine-SSA-BP model effectively improves the initialized population of uniform distribution, and reduces the problem that population intelligence algorithms tend to be premature. Conclusions: The test results show that the Sine-SSA-BP neural network has higher prediction accuracy and better stability than conventional LSTM and SVM, especially in the prediction of corners, which is in good agreement with the real ship navigation trajectory.

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Abbasi, Mostafa, and Ali Gholami. "Polynomial chaos expansion for nonlinear geophysical inverse problems." GEOPHYSICS 82, no. 4 (July 1, 2017): R259—R268. http://dx.doi.org/10.1190/geo2016-0716.1.

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There are lots of geophysical problems that include computationally expensive functions (forward models). Polynomial chaos (PC) expansion aims to approximate such an expensive equation or system with a polynomial expansion on the basis of orthogonal polynomials. Evaluation of this expansion is extremely fast because it is a polynomial function. This property of the PC expansion is of great importance for stochastic problems, in which an expensive function needs to be evaluated thousands of times. We have developed PC expansion as a novel technique to solve nonlinear geophysical problems. To better evaluate the methodology, we use PC expansion for automating the velocity analysis. For this purpose, we define the optimally picked velocity model as an optimizer of a variational integral in a semblance field. However, because computation of a variational integral with respect to a given velocity model is rather expensive, it is impossible to use stochastic methods to search for the optimal velocity model. Thus, we replace the variational integral with its PC expansion, in which computation of the new function is extremely faster than the original one. This makes it possible to perturb thousands of velocity models in a matter of seconds. We use particle swarm optimization as the stochastic optimization method to find the optimum velocity model. The methodology is tested on synthetic and field data, and in both cases, reasonable results are achieved in a rather short time.

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Wang, Zhen, Abdul Jalil M. Khalaf, Sajad Jafari, Shirin Panahi, Chunbiao Li, and Iqtadar Hussain. "A New Memristive Chaotic System with a Plane and Two Lines of Equilibria." International Journal of Bifurcation and Chaos 31, no. 05 (April 2021): 2150066. http://dx.doi.org/10.1142/s0218127421500668.

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A new 4D memristive chaotic system with an infinite number of equilibria is proposed via exhaustive computer search. Interestingly, such a new memristive system has a plane of equilibria and two other lines of equilibria. Lyapunov exponent and bifurcation analysis show that this system has chaotic solutions with coexisting attractors. The basins of attraction of the coexisting attractors show chaos, stable fixed-points, and unbounded solutions. Furthermore, the 2D parameter space of the system is explored to find the optimum values of the parameters using the ALO (Ant Lion Optimizer) optimization algorithm.

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35

Liu, Mei Rong, Yi Gang He, and Xiang Xin Li. "Fault Diagnosis of Analog Circuits Based on CFNN." Advanced Engineering Forum 6-7 (September 2012): 1045–50. http://dx.doi.org/10.4028/www.scientific.net/aef.6-7.1045.

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An analog circuits fault diagnosis method based on chaotic fuzzy neural network (CFNN) is presented. The method uses the advantage of the global movement characteristic inherent in chaos to overcome the shortcomings that BPNN is usually trapped to a local optimum and it has a low speed of convergence weights. The chaotic mapping was added into BPNN algorithm, and the initial value of the network was selected. The algorithm can effectively and reliably be used in analog circuit fault diagnosis by comparing the two methods and analyzing the results of the example.

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36

Chen, Ying, and Lian Guang Liu. "Sizing and Locating of Distributed Generations Based on Chaos Particle Swarm Optimization Algorithm." Applied Mechanics and Materials 291-294 (February 2013): 2119–23. http://dx.doi.org/10.4028/www.scientific.net/amm.291-294.2119.

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Optimal configuration of distributed generations (DGs) is an important topic in the developing of intelligent power grid. In this paper, to finding out the optimal sitting and sizing Of DGs in distribution network without considering the newly increased load nodes, an economical model is built that regards the annual minimum operating cost as the objective function. Meanwhile, in order to avoid the particles trapping in local optimum, the chaos particle swarm optimization algorithm (CPSO) is adopted. Through testing on the IEEE 33-bus radial distribution system, the analysis results showed that the algorithm is effective.

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37

Arifan, Fahmi, Deddy Kurniawan Wikanta, and Margaretha Tuti Susanti. "Kemampuan Asap Cair pada Pengawetan Ikan Bandeng Disertai Perendaman Prapengasapan dalam Larutan Mikrokapsul Oleoresin Daun Sirih." INTEK: Jurnal Penelitian 4, no. 2 (November 4, 2017): 87. http://dx.doi.org/10.31963/intek.v4i2.148.

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On this research have observed liquid smoke’s ability to pursue microbe activity, antimicrobe and antioxidant compounds in betel oleoresin, give preservation effect by pursue microorganism’s growth on Chanos-chanos forsk. Fish Submerge process by liquid smoke with betel oleoresin submerge on pre-smoking, give optimum result value of TVB 8,62 mg N/100gr, reach on submerge by betel oleoresin 6% concentration, during 15 minutes, and submerge with liquid smoke 4% concentration during 10 minutes. Value of total microbe 6,06 x 10 3 CFU. Result above has contribution with censor examination of rather hard texture and much liked flavor.

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38

BANERJEE, TANMOY, BISHWAJIT PAUL, and B. C. SARKAR. "BIFURCATION, CHAOS AND THEIR CONTROL IN A TIME-DELAY DIGITAL TANLOCK LOOP." International Journal of Bifurcation and Chaos 23, no. 08 (August 2013): 1330029. http://dx.doi.org/10.1142/s0218127413300292.

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This paper reports the detailed parameter space study of the nonlinear dynamical behaviors and their control in a time-delay digital tanlock loop (TDTL). At first, we explore the nonlinear dynamics of the TDTL in parameter space and show that beyond a certain value of loop gain parameter the system manifests bifurcation and chaos. Next, we consider two variants of the delayed feedback control (DFC) technique, namely, the time-delayed feedback control (TDFC) technique, and its modified version, the extended time-delayed feedback control (ETDFC) technique. Stability analyses are carried out to find out the stable phase-locked zone of the system for both the controlled cases. We employ two-parameter bifurcation diagrams and the Lyapunov exponent spectrum to explore the dynamics of the system in the global parameter space. We establish that the control techniques can extend the stable phase-locked region of operation by controlling the occurrence of bifurcation and chaos. We also derive an estimate of the optimum parameter values for which the controlled system has the fastest convergence time even for a larger acquisition range. The present study provides a necessary detailed parameter space study that will enable one to design an improved TDTL system.

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39

Gálvez, Jorge, Erik Cuevas, and Krishna Gopal Dhal. "A Competitive Memory Paradigm for Multimodal Optimization Driven by Clustering and Chaos." Mathematics 8, no. 6 (June 8, 2020): 934. http://dx.doi.org/10.3390/math8060934.

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Evolutionary Computation Methods (ECMs) are proposed as stochastic search methods to solve complex optimization problems where classical optimization methods are not suitable. Most of the proposed ECMs aim to find the global optimum for a given function. However, from a practical point of view, in engineering, finding the global optimum may not always be useful, since it may represent solutions that are not physically, mechanically or even structurally realizable. Commonly, the evolutionary operators of ECMs are not designed to efficiently register multiple optima by executing them a single run. Under such circumstances, there is a need to incorporate certain mechanisms to allow ECMs to maintain and register multiple optima at each generation executed in a single run. On the other hand, the concept of dominance found in animal behavior indicates the level of social interaction among two animals in terms of aggressiveness. Such aggressiveness keeps two or more individuals as distant as possible from one another, where the most dominant individual prevails as the other withdraws. In this paper, the concept of dominance is computationally abstracted in terms of a data structure called “competitive memory” to incorporate multimodal capabilities into the evolutionary operators of the recently proposed Cluster-Chaotic-Optimization (CCO). Under CCO, the competitive memory is implemented as a memory mechanism to efficiently register and maintain all possible optimal values within a single execution of the algorithm. The performance of the proposed method is numerically compared against several multimodal schemes over a set of benchmark functions. The experimental study suggests that the proposed approach outperforms its competitors in terms of robustness, quality, and precision.

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40

Li, Hui Xia, Yun Can Xue, Jian Qiang Zhang, and Qi Wen Yang. "Information Technology in an Improved Quantum Genetic Algorithm Based on Dynamic Adjustment of Quantum Rotation Angle." Advanced Materials Research 859 (December 2013): 577–81. http://dx.doi.org/10.4028/www.scientific.net/amr.859.577.

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To overcome the shortcomings of precocity and being easily trapped into local optimum of the standard quantum genetic algorithm (QGA) , Information Technology in An Improved Quantum Genetic Algorithm based on dynamic adjustment of the quantum rotation angle of quantum gate (DAAQGA) was proposed. Mutation operation using the quantum not-gate is also introduced to enhance the diversity of population. Chaos search are also introduced into the modified algorithm to improve the search accuracy. Simulation experiments have been carried and the results show that the improved algorithm has excellent performance both in the preventing premature ability and in the search accuracy.

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41

Ai, Ying, Yi Xin Su, and Yao Peng. "Optimization of Reactive Power Based on Dynamic Learning Factor Multi-Objective Particle Swarm Algorithm." Applied Mechanics and Materials 556-562 (May 2014): 3984–87. http://dx.doi.org/10.4028/www.scientific.net/amm.556-562.3984.

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. Particle swarm optimization algorithm has the defects of easy to fall into local optimum and low convergence accuracy used in reactive power optimization. To solve the problems, this paper proposed an improved particle swarm optimization algorithm based on dynamic learning factors. The two accelerations are changed with searching stage, so as to enhance the early globle search ability and the late local search ability, then to avoid local optimum; minimum particle angle method and crowded distance method are uesd to determine the global extremum in instalments, so as to improve the convergence speed and accuracy of multi-objective pareto solutions. Take the IEEE 30 bus system IEEE 118 bus system as example, the proposed method is compared with adaptive chaos particle swarm optimization (ACPSO) and NSGA-II, simulation results show that the method put forward in this paper has better convergence accuracy.

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42

Yousefi, Peyman, Gregory Courtice, Gholamreza Naser, and Hadi Mohammadi. "Nonlinear Dynamic Modeling of Urban Water Consumption Using Chaotic Approach (Case Study: City of Kelowna)." Water 12, no. 3 (March 9, 2020): 753. http://dx.doi.org/10.3390/w12030753.

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This study investigated urban water consumption complexity using chaos theory to improve forecasting performance to help optimize system management, reduce costs and improve reliability. The objectives of this study were to (1) investigate urban water distribution consumption complexity and its role in forecasting technique performance, (2) evaluate forecasting models by periodicity and lead time, and (3) propose a suitable forecasting technique based on operator applications and performance through various time scales. An urban consumption dataset obtained from the City of Kelowna (British Columbia, Canada) was used as a test case to forecast future consumption values using varying lead times under different temporal scales to identify models which may improve forecasting performance. Chaos theory techniques were employed to inform model optimization. This study attempted to address the paucity of studies on chaos theory applications in water consumption forecasting. This was accomplished by applying non-linear approximation, dynamic investigation, and phase space reconstruction for input variables, to improve the accuracy in various periodicity and lead time. To reconstruct the phase space, lag time was calculated using average mutual information for daily resolution as 17 days to reconstruct the phase space. The optimum embedding dimension and correlation exponent for the phase space were 18 and 3.5, respectively. Comparing the results, the non-linear local approximation model provided the best performance. The forecasting horizon for the models was 122 days. Moreover, phase space reconstruction improved the accuracy of the models for the different lead times. The findings of this study may improve forecasting performance and provide evidence to support further investigation of the chaotic behaviour of water consumption values over different time scales.

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Yuniarti, Tatty, Tati Nurhayati, and Agoes M. Jacoeb. "Semipurifikasi dan Karakterisasi Kolagenase dari Organ Dalam Ikan Bandeng (Channos channos, Forskal)." Jurnal Penyuluhan Perikanan dan Kelautan 4, no. 2 (December 27, 2010): 106–15. http://dx.doi.org/10.33378/jppik.v4i2.22.

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Aktivitas enzim-enzim proteolisis seperti kolagenase, dapat memecah proteinmenjadi molekul yang lebih sederhana (autolisis) mengakibatkan terjadinya pelemasandaging ikan pada fase post mortem. Penelitian perlu dilakukan untuk mengetahui sifat-sifatenzim tersebut. Tujuan dari penelitian ini adalah untuk memurnikan dan mengkarakterisasienzim kolagense dari organ dalam bandeng. Enzim kolagenase telah dapat dimurnikan dariorgan dalam bandeng (Chanos chanos, Forskal), dengan ekstraksi dan pengendapanmenggunakan ammonium sulfat. Tingkat kelipatan pemurnian yang dihasilkan 2,347 danyield adalah 35,42. Karakterisasi kolagenase menunjukkan suhu optimum 50 oC dan pHoptimum 8-9. Enzim kolagenase dapat dihambat dengan kuat oleh serine proteinaseinhibitor (PMSF)dan meningkat aktivitasnya dengan penambahan Ca2+ dan Na+, enzimkolagenase ini stabil pada 10-50 oC and pH 8-9.

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44

Talagaev, Yu V., and A. F. Tarakanov. "Suppressing chaos through optimum correction of the control parameters in a duffing-van der pol oscillator." Technical Physics Letters 32, no. 12 (December 2006): 1043–46. http://dx.doi.org/10.1134/s1063785006120145.

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45

Latifah, Emi, Putri Dwi Mulyani, and Yekti Asih Purwestri. "Lignolytic Enzyme Activity of Isolated Bacteria from Termite (Coptotermes Sp.) and Milkfish (Chanos chanos Forsskal, 1775) Guts." Biosaintifika: Journal of Biology & Biology Education 13, no. 1 (April 10, 2021): 70–76. http://dx.doi.org/10.15294/biosaintifika.v13i1.19333.

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Bacteria BSR 2, Pseudomonas alcaligenes (BSR 3), Brevibacillus parabrevis (BSR 8), Brevibacillus sp. (BSR 9), isolated from termite gut and Bacillus licheniformis (BSA B1) isolated from milkfish gut have been known to possess celluloytic activity. However, their lignolytic ability has not been known. This study aimed to determine the lignolytic ability of bacteria isolated from termit (Coptotermes sp.) and milkfish (Chanos chanos Forsskal, 1775) guts and their enzymes characterization. The qualitative test was done through the spot test method, while quantitative assay was performed spectrophotometrically at 335 nm to calculate vanillin concentration. The isolates were grown in Lignin Mineral Medium, then the optical density (OD620) were measured every 24 hours for 5 days using spectrophotometer to determine their growth profile and the best isolation time of the lignolytic enzyme. Based on results, the best lignolytic enzyme isolation time for strains Bacillus licheniformis (BSA B1) and BSR 2 were 5 days, yielding lignolytic enzyme activity of 0.961 Â± 0.168 U/mg and 2.176 Â± 0.088 U/mg respectively, Â while strains Pseudomonas alcaligenes (BSR 3), Brevibacillus parabrevis (BSR 8), and Brevibacillus sp. (BSR 9) were 4 days, yielding of 1.206 Â± 0.045 U/mg, 1.162 Â± 0.191 U/mg, and 0.896 Â± 0.108 U/mg, respectively. The strain BSR 2 showed the highest lignolytic activity compared to other strains. The optimum temperature for lignolytic enzyme activity of BSR 2 was 30 â„ƒ and the optimum pH was 7. The lignolytic enzyme activity showed that these bacterial isolates can be a chance to be used as new alternative lignolytic enzyme source in commercial bioconversion process.

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46

UEOKA, YUTA, TOMOYA SUZUKI, and SEIICHI YAMAMOTO. "ANALYSIS ON THE EFFICIENCY OF STATISTICAL MEASURES TO IDENTIFY NETWORK STRUCTURE OF CHAOS COUPLED SYSTEMS." International Journal of Modern Physics C 21, no. 08 (August 2010): 1065–79. http://dx.doi.org/10.1142/s0129183110015671.

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Real systems often show complex behavior due to interaction among many elements composing a large-scale network. To model and predict these systems, it is desired to estimate network structures by using only time-series data observed as behavior of systems. Although several kinds of estimation techniques have been proposed, the optimum technique might be different according to properties of systems. To analyze the possibility, we estimate interactions of chaos coupled systems by four typical types of estimation techniques. For numerical simulations, we adopt the coupled map lattice, which is a model of large-scale complex systems, and we modify it so as to control the degree of synchronization and the instability of systems by changing the coupling strength and the topology of interaction among elements. As results, we can confirm that the optimum technique depends on properties of system, and then we clarify the reason from the viewpoint of synchronization and the Lyapunov exponents. Moreover, as an application, we predict future behavior of each element with new prediction model based on estimated interactions, and we demonstrate the efficiency of this prediction method.

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47

Jia, Li, Bao-guo Fan, Ben Li, Yu-Xing Yao, Rui-Peng Huo, Rui Zhao, Xiao-Lei Qiao, and Yan Jin. "Effects of Pyrolysis Mode and Particle Size on the Microscopic Characteristics and Mercury Adsorption Characteristics of Biomass Char." BioResources 13, no. 3 (2018): 5450–71. http://dx.doi.org/10.15376/biores.13.3.5450-5471.

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Biomass chars (bio-chars) prepared under two pyrolysis modes and with four particle size ranges were investigated. The pyrolysis modes included isothermal pyrolysis and non-isothermal pyrolysis with three heating rates (5 °C/min, 10 °C/min, and 15 °C/min). The particle size ranges were 58-75 μm, 75-106 μm, 106-150 μm, and 150-270 μm. The pyrolysis characteristics, pore structures, surface morphologies, and functional groups of the bio-chars were characterized by TGA, specific surface area and porosity analyses, SEM, and FTIR. The mercury adsorption was further explored by the adsorption kinetics. The results established the optimum pyrolysis conditions for mercury adsorption: pyrolysis temperature of 600 °C, heating rate of 10 °C/min, and particle size of 58-75 μm. In addition, the mercury adsorption processes were affected by both physical adsorption and chemical adsorption. Furthermore, the rate constants of the pseudo-first-order and pseudo-second-order models gradually increased with decreasing particle size.

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48

Li, Xin Ran, and Yan Xia Jin. "A Quantum-Behaved Particle Swarm Algorithm Combined with Chaotic Mutation." Advanced Materials Research 605-607 (December 2012): 2442–46. http://dx.doi.org/10.4028/www.scientific.net/amr.605-607.2442.

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The article puts forward an improved PSO algorithm based on the quantum behavior——CMQPSO algorithm to improve premature convergence problem in particle swarm algorithm. The new algorithm first adopts Tent mapping initialization of particle swarm, searches each particle chaos, and strengthens the diversity of searching. Secondly, a method of effective judgment of early stagnation is embedded in the algorithm. Once the early maturity is retrieved, the algorithm mutates particles to jump out of the local optimum particle according to the structure mutation so as to reduce invalid iteration. The calculation of classical function test shows that the improved algorithm is superior to classical PSO algorithm and quantum-behaved PSO algorithm.

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49

Parkhomenko, Yu N., B. Spektor, and J. Shamir. "Anomalous dynamics of active mode-locking in ring lasers with semiconductor optic amplifiers." Journal of Nonlinear Optical Physics & Materials 26, no. 02 (June 2017): 1750017. http://dx.doi.org/10.1142/s0218863517500175.

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The pulses development dynamics, including their bifurcation into two-pulse complexes, was investigated in ring semiconductor lasers with amplitude modulation, operating on harmonics. New unusual properties of active mode-locking were revealed. They indicate significantly different dynamics of lasers operating on the first harmonic and those operating on any higher harmonic. The domain of control parameters for single pulses of higher harmonics is split into two domains: the dynamic boundary layer of finite width adjacent to the bifurcation line and the domain of dynamic chaos. Such layers engender stable dynamic sync-bands. We found conditions to implement energy-efficient sync-bands with optimum pulse parameters.

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50

Chen, Shuai, and Zhe Kan. "Image Reconstruction Algorithm for Electrical Capacitance Tomography Based on Constrained Particle Swarm Optimization." Journal of Physics: Conference Series 2404, no. 1 (December 1, 2022): 012058. http://dx.doi.org/10.1088/1742-6596/2404/1/012058.

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Abstract When the particle swarm is active, the robustness of the system is quite great, which is very useful for solving ill-conditioned problems like picture reconstruction. In the reconstructed image, however, the large number of pixels results in the large dimension of particles, making it harder for particles to attain the ideal solution during the optimization process. A constraint condition is applied to the position of particles to solve this problem. The image reconstruction algorithm regularized by Tikhonov is used as the particle position reference to constrain the particles to search within a certain range of the algorithm, and the penalty function is used to solve the problem to improve the particle search speed. For the inertia weight of particle swarm, this paper uses linear decreasing weight to realize its adaptive dynamic adjustment, which improves the flexibility of the algorithm. When chaos operator is added to the particle swarm location search process, if the particle is trapped in a local optimum, the chaos variable will fluctuate within a certain range, thus reducing the error rate of the optimal solution. The experimental comparison results illustrate that the modified particle swarm optimization technique for the image reconstruction of Electrical Capacitance Tomography outperforms the classic LBP and Tikhonov algorithms in terms of accuracy and efficiency.

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