Artigos de revistas: "Split algorithm"

1

Liang, Liang. "A Fusion Multiobjective Empire Split Algorithm." Journal of Control Science and Engineering 2020 (December 14, 2020): 1–14. http://dx.doi.org/10.1155/2020/8882086.

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In the last two decades, swarm intelligence optimization algorithms have been widely studied and applied to multiobjective optimization problems. In multiobjective optimization, reproduction operations and the balance of convergence and diversity are two crucial issues. Imperialist competitive algorithm (ICA) and sine cosine algorithm (SCA) are two potential algorithms for handling single-objective optimization problems, but the research of them in multiobjective optimization is scarce. In this paper, a fusion multiobjective empire split algorithm (FMOESA) is proposed. First, an initialization operation based on opposition-based learning strategy is hired to generate a good initial population. A new reproduction of offspring is introduced, which combines ICA and SCA. Besides, a novel power evaluation mechanism is proposed to identify individual performance, which takes into account both convergence and diversity of population. Experimental studies on several benchmark problems show that FMOESA is competitive compared with the state-of-the-art algorithms. Given both good performance and nice properties, the proposed algorithm could be an alternative tool when dealing with multiobjective optimization problems.

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Ortiz Díaz, Agustín Alejandro, Isvani Inocencio Frías Blanco, Laura María Palomino Mariño, and Fabiano Baldo. "An Online Tree-Based Approach for Mining Non-Stationary High-Speed Data Streams." Revista de Informática Teórica e Aplicada 27, no. 1 (2020): 36–47. http://dx.doi.org/10.22456/2175-2745.90822.

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This paper presents a new learning algorithm for inducing decision trees from data streams. In these domains, large amounts of data are constantly arriving over time, possibly at high speed. The proposed algorithm uses a top-down induction method for building trees, splitting leaf nodes recursively, until none of them can be expanded. The new algorithm combines two split methods in the tree induction. The first method is able to guarantee, with statistical significance, that each split chosen would be the same as that chosen using infinite examples. By doing so, it aims at ensuring that the tree induced online is close to the optimal model. However, this split method often needs too many examples to make a decision about the best split, which delays the accuracy improvement of the online predictive learning model. Therefore, the second method is used to split nodes more quickly, speeding up the tree growth. The second split method is based on the observation that larger trees are able to store more information about the training examples and to represent more complex concepts. The first split method is also used to correct splits previously suggested by the second one, when it has sufficient evidence. Finally, an additional procedure rebuilds the tree model according to the suggestions made with an adequate level of statistical significance. The proposed algorithm is empirically compared with several well-known induction algorithms for learning decision trees from data streams. In the tests it is possible to observe that the proposed algorithm is more competitive in terms of accuracy and model size using various synthetic and real world datasets.

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Pinker, Rachel T., Donglian Sun, Meng-Pai Hung, Chuan Li, and Jeffrey B. Basara. "Evaluation of Satellite Estimates of Land Surface Temperature from GOES over the United States." Journal of Applied Meteorology and Climatology 48, no. 1 (2009): 167–80. http://dx.doi.org/10.1175/2008jamc1781.1.

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Abstract A comprehensive evaluation of split-window and triple-window algorithms to estimate land surface temperature (LST) from Geostationary Operational Environmental Satellites (GOES) that were previously described by Sun and Pinker is presented. The evaluation of the split-window algorithm is done against ground observations and against independently developed algorithms. The triple-window algorithm is evaluated only for nighttime against ground observations and against the Sun and Pinker split-window (SP-SW) algorithm. The ground observations used are from the Atmospheric Radiation Measurement Program (ARM) Central Facility, Southern Great Plains site (April 1997–March 1998); from five Surface Radiation Budget Network (SURFRAD) stations (1996–2000); and from the Oklahoma Mesonet. The independent algorithms used for comparison include the National Oceanic and Atmospheric Administration/National Environmental Satellite, Data and Information Service operational method and the following split-window algorithms: that of Price, that of Prata and Platt, two versions of that of Ulivieri, that of Vidal, two versions of that of Sobrino, that of Coll and others, the generalized split-window algorithm as described by Becker and Li and by Wan and Dozier, and the Becker and Li algorithm with water vapor correction. The evaluation against the ARM and SURFRAD observations indicates that the LST retrievals from the SP-SW algorithm are in closer agreement with the ground observations than are the other algorithms tested. When evaluated against observations from the Oklahoma Mesonet, the triple-window algorithm is found to perform better than the split-window algorithm during nighttime.

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4

Delsarte, P., and Y. Genin. "The split Levinson algorithm." IEEE Transactions on Acoustics, Speech, and Signal Processing 34, no. 3 (1986): 470–78. http://dx.doi.org/10.1109/tassp.1986.1164830.

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Hidayat, Trifenaus Prabu, and Andre Sugioko. "Performance Analyzes of Bee Colony Split-Plot Algorithm." International Journal of Information and Education Technology 5, no. 7 (2015): 549–52. http://dx.doi.org/10.7763/ijiet.2015.v5.566.

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6

Jambunathan, Suriya Prakash. "A Machine Learning-Based Approach for Antenna Design Using Class_Reg Algorithm Optimized Using Genetic Algorithm." International Journal for Research in Applied Science and Engineering Technology 9, no. 11 (2021): 1682–86. http://dx.doi.org/10.22214/ijraset.2021.39097.

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Abstract: Microstrip patch antennas are predominantly in use in mobile communication and healthcare. Their performances are even improved, using Split-Ring Resonator cells. But finding the ideal dimensions of the microstrip patch antenna and calculating the correct number and size of the split ring resonator cells consume a lot of time when we use Electromagnetic Simulation software to design first and then simulate. Using the pre-calculated results of certain sets of microstrip patch antennas with split ring resonators, a machine learning model can be trained and hence be used to predict the antenna metrics when the dimensions are specified. When the machine learning algorithms are combined with feature-optimization algorithms such as the Genetic Algorithm, the efficiency and performance can be improved further. Keywords: Machine Learning, Micro-strip Patch Antenna, Genetic algorithm, Split Ring Resonator.

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Cui, Ying Hua, Yu Ping Zhao, Hui Yang Wang, and Jin He Zhou. "Pre-Split Anti-Collision Binary Tree Algorithm." Applied Mechanics and Materials 220-223 (November 2012): 2403–6. http://dx.doi.org/10.4028/www.scientific.net/amm.220-223.2403.

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In RFID system, reducing the frequency of collisions is very important for fast tag identification. In this paper, we proposed a pre-split anti-collision algorithm based on binary tree algorithm. The proposed scheme pre-splits the tags into different groups before the reader detects the first tag. Simulation results indicate that the modified algorithm can achieve much better performance than the conventional one.

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8

Huang, Zheng, Yanting Zhang, Lin Wang, Jingyu Xu, and Yunlong Zheng. "Research on multi-objective parameter optimization of split flow dual flash thermodynamic cycle." Journal of Physics: Conference Series 2728, no. 1 (2024): 012008. http://dx.doi.org/10.1088/1742-6596/2728/1/012008.

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Abstract In addition to considering the intermediate pressure variables, the split flow double flash thermodynamic cycle also needs to consider the operating conditions and split flow coefficient of the cycle. Traditional algorithms require too much computation and have a longer response time. Faced with sudden operating conditions or changes in production conditions, it is difficult to quickly re-optimize the intermediate parameters of the split flow double flash thermal cycle and carry out corresponding system control. This article uses intelligent optimization algorithms instead of global search methods to optimize multi-objective parameters in a split flow double flash thermodynamic cycle. By summarizing and analyzing the characteristics of algorithms such as SIO, EA, and ANN, it is believed that the GWO algorithm in the SIO class is the most suitable for multi-objective parameter optimization of the split flow double flash thermal cycle. It is combined with the SA optimization algorithm to propose the SA-GWO algorithm with faster optimization speed and higher optimization accuracy, taking the initial position of the wolf pack as the optimization objective. Combined with the cycle thermodynamic model, a multi-objective parameter optimization model for the split flow double flash thermal cycle is established.

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9

Ching, P. C., and K. F. Wan. "Generalised split structure adaptive algorithm." Electronics Letters 31, no. 24 (1995): 2084–85. http://dx.doi.org/10.1049/el:19951435.

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Jin, C., L. J. Lu, and J. N. Min. "A two-stage construction heuristic approach for vehicle routing problem with split deliveries and pickups: Case studies and performance comparison." Advances in Production Engineering & Management 17, no. 1 (2022): 121–33. http://dx.doi.org/10.14743/apem2022.1.425.

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The vehicle routing problem with split deliveries and pickups is a hot research topic in recent years, where a customer can be served multiple times with split deliveries and pickups. The objective is to minimize the travel distance, use the fewest number of vehicles and increase the load rate, which will further reduce the carbon emissions that damage the environment. In this paper, we use a two-stage construction heuristic approach to solve this problem. First, partitioning algorithms based on the multi-restart-iterative sweep algorithm are adopted to partition the customer domain into sub-domains according to the vehicle capacity, and to determine the split points and the corresponding values. Second, a modified Clarke-Wright savings algorithm is used to check the possibility of each point in each route based on the load of each point and the vehicle load limitation. The three case studies with 12 instances per each from the reconstructed Solomon benchmark datasets were conducted to evaluate the effectiveness and feasibility of the proposed approaches-Unsplit, Both-Split and Enhanced-Both-Split. The comparison among these approaches reveals that the splits reduce the total travel cost and vehicles used, and increase the average loading rate considerably, especially when customers have larger demand values. Our computation results proves that the vehicle routing problem with split deliveries and pickups is highly beneficial for transportation and logistics enterprises.

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11

YAO, YONGHONG, NASEER SHAHZAD, MIHAI POSTOLACHE, and JEN-CHIH YAO. "Convergence of self-adaptive Tseng-type algorithms for split variational inequalities and fixed point problems." Carpathian Journal of Mathematics 40, no. 3 (2024): 753–68. http://dx.doi.org/10.37193/cjm.2024.03.14.

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In this paper, we survey iterative algorithms for solving split variational inequalities and fixed point problems in Hilbert spaces. The investigated split problem is involved in two pseudomonotone operators and two pseudocontractive operators. We propose a self-adaptive Tseng-type algorithm for finding a solution of the split problem. Strong convergence of the suggested algorithm is shown under weaker conditions than sequential weak-to-weak continuity imposed on two pseudomonotone operators.

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12

Meng, Xiangchen, Jie Cheng, Shaohua Zhao, Sihan Liu, and Yunjun Yao. "Estimating Land Surface Temperature from Landsat-8 Data using the NOAA JPSS Enterprise Algorithm." Remote Sensing 11, no. 2 (2019): 155. http://dx.doi.org/10.3390/rs11020155.

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Land surface temperature (LST) is one of the key parameters in hydrology, meteorology, and the surface energy balance. The National Oceanic and Atmospheric Administration (NOAA) Joint Polar Satellite System (JPSS) Enterprise algorithm is adapted to Landsat-8 data to obtain the estimate of LST. The coefficients of the Enterprise algorithm were obtained by linear regression using the analog data produced by comprehensive radiative transfer modeling. The performance of the Enterprise algorithm was first tested by simulation data and then validated by ground measurements. In addition, the accuracy of the Enterprise algorithm was compared to the generalized split-window algorithm and the split-window algorithm of Sobrino et al. (1996). The validation results indicate the Enterprise algorithm has a comparable accuracy to the other two split-window algorithms. The biases (root mean square errors) of the Enterprise algorithm were 1.38 (3.22), 1.01 (2.32), 1.99 (3.49), 2.53 (3.46), and −0.15 K (1.11 K) at the SURFRAD, HiWATER_A, HiWATER_B, HiWATER_C sites and BanGe site, respectively, whereas those values were 1.39 (3.20), 1.0 (2.30), 1.93 (3.48), 2.53 (3.35), and −0.35 K (1.16 K) for the generalized split-window algorithm, 1.45 (3.39), 1.08 (2.41), 2.16 (3.67), 2.52 (3.58), and 0.02 K (1.12 K) for the split-window algorithm of Sobrino, respectively. This study provides an alternative method to estimate LST from Landsat-8 data.

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Zhu, Wei, Shi Shu, and Lizhi Cheng. "An Efficient Proximity Point Algorithm for Total-Variation-Based Image Restoration." Advances in Applied Mathematics and Mechanics 6, no. 2 (2014): 145–64. http://dx.doi.org/10.4208/aamm.2013.m175.

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AbstractIn this paper, we propose a fast proximity point algorithm and apply it to total variation (TV) based image restoration. The novel method is derived from the idea of establishing a general proximity point operator framework based on which new first-order schemes for total variation (TV) based image restoration have been proposed. Many current algorithms for TV-based image restoration, such as Chambolle’s projection algorithm, the split Bregman algorithm, the Bermúdez-Moreno algorithm, the Jia-Zhao denoising algorithm, and the fixed point algorithm, can be viewed as special cases of the new first-order schemes. Moreover, the convergence of the new algorithm has been analyzed at length. Finally, we make comparisons with the split Bregman algorithm which is one of the best algorithms for solving TV-based image restoration at present. Numerical experiments illustrate the efficiency of the proposed algorithms.

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14

Mejmaa, Bilal, Chakir Aqil, Ismail Akharraz, and Abdelaziz Ahaitouf. "Implementation of a Reduced Decoding Algorithm Complexity for Quasi-Cyclic Split-Row Threshold Low-Density Parity-Check Decoders." Information 15, no. 11 (2024): 684. http://dx.doi.org/10.3390/info15110684.

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We propose two decoding algorithms for quasi-cyclic LDPC codes (QC-LDPC) and implement the more efficient one in this paper. These algorithms depend on the split row for the layered decoding method applied to the Min-Sum (MS) algorithm. We designate the first algorithm “Split-Row Layered Min-Sum” (SRLMS), and the second algorithm “Split-Row Threshold Layered Min-Sum” (SRTLMS). A threshold message passes from one partition to another in SRTLMS, minimizing the gap from the MS and achieving a binary error rate of 3 × 10−5 with Imax = 4 as the maximum number of iterations, resulting in a decrease of 0.25 dB. The simulation’s findings indicate that the SRTLMS is the most efficient variant decoding algorithm for LDPC codes, thanks to its compromise between performance and complexity. This paper presents the two invented algorithms and a comprehensive study of the co-design and implementation of the SRTLMS algorithm. We executed the implementation on a Xilinx Kintex-7 XC7K160 FPGA, achieving a maximum operating frequency of 101 MHz and a throughput of 606 Mbps.

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Wang, Jian, Sheng Bi, Wenkang Liu, et al. "Stitching Locally Fitted T-Splines for Fast Fitting of Large-Scale Freeform Point Clouds." Sensors 23, no. 24 (2023): 9816. http://dx.doi.org/10.3390/s23249816.

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Parametric splines are popular tools for precision optical metrology of complex freeform surfaces. However, as a promising topologically unconstrained solution, existing T-spline fitting techniques, such as improved global fitting, local fitting, and split-connect algorithms, still suffer the problems of low computational efficiency, especially in the case of large data scales and high accuracy requirements. This paper proposes a speed-improved algorithm for fast, large-scale freeform point cloud fitting by stitching locally fitted T-splines through three steps of localized operations. Experiments show that the proposed algorithm produces a three-to-eightfold efficiency improvement from the global and local fitting algorithms, and a two-to-fourfold improvement from the latest split-connect algorithm, in high-accuracy and large-scale fitting scenarios. A classical Lena image study showed that the algorithm is at least twice as fast as the split-connect algorithm using fewer than 80% control points of the latter.

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Jia, Huijuan, Shufen Liu, and Yazheng Dang. "An Inertial Accelerated Algorithm for Solving Split Feasibility Problem with Multiple Output Sets." Journal of Mathematics 2021 (November 5, 2021): 1–12. http://dx.doi.org/10.1155/2021/6252984.

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The paper proposes an inertial accelerated algorithm for solving split feasibility problem with multiple output sets. To improve the feasibility, the algorithm involves computing of projections onto relaxed sets (half spaces) instead of computing onto the closed convex sets, and it does not require calculating matrix inverse. To accelerate the convergence, the algorithm adopts self-adaptive rules and incorporates inertial technique. The strong convergence is shown under some suitable conditions. In addition, some newly derived results are presented for solving the split feasibility problem and split feasibility problem with multiple output sets. Finally, numerical experiments illustrate that the algorithm converges more quickly than some existing algorithms. Our results extend and improve some methods in the literature.

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Lohawech, Panisa, Anchalee Kaewcharoen, and Ali Farajzadeh. "Convergence Theorems for the Variational Inequality Problems and Split Feasibility Problems in Hilbert Spaces." International Journal of Mathematics and Mathematical Sciences 2021 (June 2, 2021): 1–7. http://dx.doi.org/10.1155/2021/9980309.

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In this paper, we establish an iterative algorithm by combining Yamada’s hybrid steepest descent method and Wang’s algorithm for finding the common solutions of variational inequality problems and split feasibility problems. The strong convergence of the sequence generated by our suggested iterative algorithm to such a common solution is proved in the setting of Hilbert spaces under some suitable assumptions imposed on the parameters. Moreover, we propose iterative algorithms for finding the common solutions of variational inequality problems and multiple-sets split feasibility problems. Finally, we also give numerical examples for illustrating our algorithms.

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Anita Desiani, Annisa Aulia Lestari, and Lucy Chania Agatha. "Analisis Perbandingan Klasifikasi Penyakit Jantung Menggunakan Algoritma Nai ̈ve Bayes dan Algoritma Logistic Regression." Jurnal Rekayasa Elektro Sriwijaya 5, no. 2 (2024): 82–90. http://dx.doi.org/10.36706/jres.v5i2.104.

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Heart disease is a condition where parts of the heart are damaged. Thus, early detection is needed. One of them is by doing data mining classification using the Naïve Bayes and Logistic Regression algorithms. This research will compare Naïve Bayes and Logistic Regression algorithms through the training percentage split and k-fold cross validation methods to get the best classification results in detecting heart disease by calculating the average value of precision, recall, and accuracy. The Naïve Bayes algorithm with the training percentage split method produces average values for precision, recall, and accuracy of 83%, 82.5% and 81%, while the Naïve Bayes algorithm with k-fold cross validation provides average values for precision, recall, and accuracy of 83.5%, 85.5% and 83%. Logistic Regression algorithm with percentage split training method produces average values for precision, recall, and accuracy of 73.5%, 73.5% and 73%, while Logistic Regression algorithm using k-fold cross validation produces average values for precision, recall, and accuracy of 84%, 83.5% and 84%. This shows that the Naïve Bayes algorithm using percentage split is better than Logistic Regression, but when using the k-fold cross validation method, the Logistic Regression algorithm has a significant increase compared to Naïve Bayes. So that to classify heart disease is better with the Logistic Regression Algorithm with the k-fold cross validation method.

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Wang, Xinglong, Jing Zhao, and Dingfang Hou. "Modified Relaxed CQ Iterative Algorithms for the Split Feasibility Problem." Mathematics 7, no. 2 (2019): 119. http://dx.doi.org/10.3390/math7020119.

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The split feasibility problem models inverse problems arising from phase retrievals problems and intensity-modulated radiation therapy. For solving the split feasibility problem, Xu proposed a relaxed CQ algorithm that only involves projections onto half-spaces. In this paper, we use the dual variable to propose a new relaxed CQ iterative algorithm that generalizes Xu’s relaxed CQ algorithm in real Hilbert spaces. By using projections onto half-spaces instead of those onto closed convex sets, the proposed algorithm is implementable. Moreover, we present modified relaxed CQ algorithm with viscosity approximation method. Under suitable conditions, global weak and strong convergence of the proposed algorithms are proved. Some numerical experiments are also presented to illustrate the effectiveness of the proposed algorithms. Our results improve and extend the corresponding results of Xu and some others.

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Li, Xiaochun, Xiaoxiao Liu, and Fugen Gao. "The Ball-Relaxed Gradient-Projection Algorithm for Split Feasibility Problem." Journal of Function Spaces 2022 (April 12, 2022): 1–6. http://dx.doi.org/10.1155/2022/9991466.

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In this paper, we concern with the split feasibility problem (SFP) whenever the convex sets involved are composed of level sets. By applying Gradient-projection algorithm which is used to solve constrained convex minimization problem of a real valued convex function, we construct two new algorithms for the split feasibility problem and prove that both of them are convergent weakly to a solution of the feasibility problem. In the end, as an application, we obtain a new algorithm for solving the split equality problem.

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Wang, Lijuan, Ni Guo, Wei Wang, and Hongchao Zuo. "Optimization of the Local Split-Window Algorithm for FY-4A Land Surface Temperature Retrieval." Remote Sensing 11, no. 17 (2019): 2016. http://dx.doi.org/10.3390/rs11172016.

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FY-4A is a second generation of geostationary orbiting meteorological satellite, and the successful launch of FY-4A satellite provides a new opportunity to obtain diurnal variation of land surface temperature (LST). In this paper, different underlying surfaces-observed data were applied to evaluate the applicability of the local split-window algorithm for FY-4A, and the local split-window algorithm parameters were optimized by the artificial intelligent particle swarm optimization (PSO) algorithm to improve the accuracy of retrieved LST. Results show that the retrieved LST can efficiently reproduce the diurnal variation characteristics of LST. However, the estimated values deviate hugely from the observed values when the local split-window algorithms are directly used to process the FY-4A satellite data, and the root mean square errors (RMSEs) are approximately 6K. The accuracy of the retrieved LST cannot be effectively improved by merely modifying the emissivity-estimated model or optimizing the algorithm. Based on the measured emissivity, the RMSE of LST retrieved by the optimized local split-window algorithm is reduced to 3.45 K. The local split-window algorithm is a simple and easy retrieval approach that can quickly retrieve LST on a regional scale and promote the application of FY-4A satellite data in related fields.

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García-Martín, Eva, Niklas Lavesson, Håkan Grahn, Emiliano Casalicchio, and Veselka Boeva. "Energy-aware very fast decision tree." International Journal of Data Science and Analytics 11, no. 2 (2021): 105–26. http://dx.doi.org/10.1007/s41060-021-00246-4.

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AbstractRecently machine learning researchers are designing algorithms that can run in embedded and mobile devices, which introduces additional constraints compared to traditional algorithm design approaches. One of these constraints is energy consumption, which directly translates to battery capacity for these devices. Streaming algorithms, such as the Very Fast Decision Tree (VFDT), are designed to run in such devices due to their high velocity and low memory requirements. However, they have not been designed with an energy efficiency focus. This paper addresses this challenge by presenting the nmin adaptation method, which reduces the energy consumption of the VFDT algorithm with only minor effects on accuracy. nmin adaptation allows the algorithm to grow faster in those branches where there is more confidence to create a split, and delays the split on the less confident branches. This removes unnecessary computations related to checking for splits but maintains similar levels of accuracy. We have conducted extensive experiments on 29 public datasets, showing that the VFDT with nmin adaptation consumes up to 31% less energy than the original VFDT, and up to 96% less energy than the CVFDT (VFDT adapted for concept drift scenarios), trading off up to 1.7 percent of accuracy.

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Leng, Kaijing, and Leilei Deng. "Direction of arrival and target scale estimation based on split beamforming algorithm." Journal of Physics: Conference Series 2290, no. 1 (2022): 012110. http://dx.doi.org/10.1088/1742-6596/2290/1/012110.

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Abstract Based on the theory of split beamforming algorithm and the experimental data collected by circular array, this paper analyzes the characteristics of DOA and target size estimation. In this paper, the signal receiving model of planar circular array and the split beamforming algorithm are studied. Then, based on the data collected from the lake experiment, the DOA estimation results of conventional beamforming algorithm, multiple signal classification algorithm and split beamforming algorithm are analyzed, and the target scale estimation results of split beamforming algorithm is analyzed. The experimental data analysis shows that the split beamforming algorithm has good direction finding stability, and the target scale estimation error based on the split beamforming algorithm is small.

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Zhao, Jing, and Hang Zhang. "Solving Split Common Fixed-Point Problem of Firmly Quasi-Nonexpansive Mappings without Prior Knowledge of Operators Norms." Abstract and Applied Analysis 2014 (2014): 1–9. http://dx.doi.org/10.1155/2014/389689.

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Very recently, Moudafi introduced alternating CQ-algorithms and simultaneous iterative algorithms for the split common fixed-point problem concerned two bounded linear operators. However, to employ Moudafi’s algorithms, one needs to know a prior norm (or at least an estimate of the norm) of the bounded linear operators. To estimate the norm of an operator is very difficult, if it is not an impossible task. It is the purpose of this paper to introduce a viscosity iterative algorithm with a way of selecting the stepsizes such that the implementation of the algorithm does not need any prior information about the operator norms. We prove the strong convergence of the proposed algorithms for split common fixed-point problem governed by the firmly quasi-nonexpansive operators. As a consequence, we obtain strong convergence theorems for split feasibility problem and split common null point problems of maximal monotone operators. Our results improve and extend the corresponding results announced by many others.

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Rathee, Savita, and Monika Swami. "Algorithm for split variational inequality, split equilibrium problem and split common fixed point problem." AIMS Mathematics 7, no. 5 (2022): 9325–38. http://dx.doi.org/10.3934/math.2022517.

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<abstract><p>The main aim of this manuscript is to work on the split equilibrium problem with the combined results of the fixed point problem and split variational inequality problem. This paper is an extension of the recent work of Lohawech et al. We proposed a sequence that converges weakly to the common solution of all the three problems mentioned earlier. In the end, we supply some direct consequences of the main result, as the paper is an extension of various existing results.</p></abstract>

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Yu, Youli, Shin Min Kang, and Young Chel Kwun. "Relaxed Extragradient Algorithms for the Split Feasibility Problem." Journal of Applied Mathematics 2014 (2014): 1–10. http://dx.doi.org/10.1155/2014/468079.

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The purpose of this paper is to introduce a new relaxed extragradient algorithms for the split feasibility problem. Our relaxed extragradient algorithm is new and it generalized some results for solving the split feasibility problem.

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Karahan, Ibrahim, and Lateef Olakunle Jolaoso. "An iterative algorithm for the system of split mixed equilibrium problem." Demonstratio Mathematica 53, no. 1 (2020): 309–24. http://dx.doi.org/10.1515/dema-2020-0027.

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AbstractIn this article, a new problem that is called system of split mixed equilibrium problems is introduced. This problem is more general than many other equilibrium problems such as problems of system of equilibrium, system of split equilibrium, split mixed equilibrium, and system of split variational inequality. A new iterative algorithm is proposed, and it is shown that it satisfies the weak convergence conditions for nonexpansive mappings in real Hilbert spaces. Also, an application to system of split variational inequality problems and a numeric example are given to show the efficiency of the results. Finally, we compare its rate of convergence other algorithms and show that the proposed method converges faster.

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GEORGE, ALAN D., and KEONWOOK KIM. "PARALLEL ALGORITHMS FOR SPLIT-APERTURE CONVENTIONAL BEAMFORMING." Journal of Computational Acoustics 07, no. 04 (1999): 225–44. http://dx.doi.org/10.1142/s0218396x99000151.

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Quiet submarine threats and high clutter in the littoral undersea environment increase the processing demands on beamforming arrays, particularly for applications which require in-array autonomous operation. Whereas traditional single-aperture beamforming approaches may falter, the Split-Aperture Conventional Beamforming (SA-CBF) algorithm can be used to meet stringent requirements for more precise bearing estimation. Moreover, by coupling each transducer node with a microprocessor, parallel processing of the split-aperture beamformer on a distributed system can glean advantages in execution speed, fault tolerance, scalability, and cost. In this paper, parallel algorithms for SA-CBF are introduced using coarse-grained and medium-grained forms of decomposition. Performance results from parallel and sequential algorithms are presented using a distributed system testbed comprised of a cluster of workstations connected by a high-speed network. The execution times, parallel efficiencies, and memory requirements of each parallel algorithm are presented and analyzed. The results of these analyses demonstrate that parallel in-array processing holds the potential to meet the needs of future advanced sonar beamforming algorithms in a scalable fashion.

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Ma, Xiaoxuan, and Chao Liu. "Improved Ant Colony Algorithm for the Split Delivery Vehicle Routing Problem." Applied Sciences 14, no. 12 (2024): 5090. http://dx.doi.org/10.3390/app14125090.

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The split delivery vehicle routing problem (SDVRP) is a classic combinatorial optimization problem, which is usually solved using a heuristic algorithm. The ant colony optimization algorithm is an excellent heuristic algorithm that has been successfully applied to solve various practical problems, and it has achieved good results. However, in the existing ant colony optimization algorithms, there are issues with weak targeting of different customer selection strategies, difficulty in balancing convergence speed and global search ability, and a predisposition to become trapped in local optima. To solve these problems, this paper proposes an improved ant colony algorithm (IACA). First, in terms of customer point selection, the initial customer and noninitial customer selection strategies are proposed for different customers, and the adaptive selection threshold is designed. Second, in terms of pheromone processing, an initial pheromone distribution method based on a greedy strategy, a pheromone backtracking mechanism, and an adaptive pheromone volatile factor are proposed. Finally, based on the 2-opt local search method, vehicle path self-search and intervehicle path search are proposed to further improve the quality of the solution. This paper tests the performance of the IACA on datasets of different scales. The experimental results show that compared with the clustering algorithm, artificial bee colony algorithm, particle swarm optimization algorithm, traditional ant colony algorithm, and other algorithms, the IACA can achieve more competitive results. Specifically, compared to the path length calculated by other algorithms, the path length calculated by IACA decreased by an average of 1.58%, 4.28%, and 3.64% in small, medium, and large-scale tests, respectively.

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Li, Meixia, Xueling Zhou, and Wenchao Wang. "Internal Perturbation Projection Algorithm for the Extended Split Equality Problem and the Extended Split Equality Fixed Point Problem." Journal of Function Spaces 2020 (June 3, 2020): 1–15. http://dx.doi.org/10.1155/2020/6034754.

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In this article, we study the extended split equality problem and extended split equality fixed point problem, which are extensions of the convex feasibility problem. For solving the extended split equality problem, we present two self-adaptive stepsize algorithms with internal perturbation projection and obtain the weak and the strong convergence of the algorithms, respectively. Furthermore, based on the operators being quasinonexpansive, we offer an iterative algorithm to solve the extended split equality fixed point problem. We introduce a way of selecting the stepsize which does not need any prior information about operator norms in the three algorithms. We apply our iterative algorithms to some convex and nonlinear problems. Finally, several numerical results are shown to confirm the feasibility and efficiency of the proposed algorithms.

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XIE, Jun. "Modified Split-Merge image segmentation algorithm." Journal of Computer Applications 28, no. 7 (2008): 1744–46. http://dx.doi.org/10.3724/sp.j.1087.2008.01744.

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Chi-Hsin Wu and A. E. Yagle. "The gradient adaptive split lattice algorithm." IEEE Transactions on Signal Processing 42, no. 2 (1994): 441–43. http://dx.doi.org/10.1109/78.275623.

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SltODRAS, A. N., and C. A. CHRISTOPOULOS. "Split-radix fast cosine transform algorithm." International Journal of Electronics 74, no. 4 (1993): 513–22. http://dx.doi.org/10.1080/00207219308925854.

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Takahashi, D. "An extended split-radix FFT algorithm." IEEE Signal Processing Letters 8, no. 5 (2001): 145–47. http://dx.doi.org/10.1109/97.917698.

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Bi, Guoan, and Yangqiu Chen. "Split-radix algorithm for 2D DFT." Electronics Letters 33, no. 3 (1997): 203. http://dx.doi.org/10.1049/el:19970170.

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Ramdhani, Yudi, Cakra Mahendra Putra, and Doni Purnama Alamsyah. "Heart failure prediction based on random forest algorithm using genetic algorithm for feature selectio." International Journal of Reconfigurable and Embedded Systems (IJRES) 12, no. 2 (2023): 205. http://dx.doi.org/10.11591/ijres.v12.i2.pp205-214.

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A disorder or illness called heart failure results in the heart becoming weak or damaged. In order to avoid heart failure early on, it is crucial to understand the causes of heart failure. Based on validation, two experimental processing steps will be applied to the dataset of clinical records related to heart failure. Testing will be done in the first step utilizing six different classification algorithms, including K-nearest neighbor, neural network, random forest, decision tree, Naïve Bayes, and support vector machine (SVM). Cross-validation was employed to conduct the test. According to the results, the random forest algorithm performed better than the other five algorithms in tests employing the algorithm. Subsequent testing uses an algorithm with the best accuracy value, which will then be tested again using split validation with varying split ratios and genetic algorithms as a selection feature. The value generated from testing using the genetic algorithm selection feature is better than the random forest algorithm alone, which is recorded to produce an accuracy value of 93.36% in predicting the survival of heart failure patients.

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BI, GUOAN, A. C. KOT, and ZIHOU MENG. "GENERALISED SPLIT-RADIX ALGORITHMS FOR DFT." Journal of Circuits, Systems and Computers 08, no. 03 (1998): 405–9. http://dx.doi.org/10.1142/s0218126698000201.

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This letter presents a general split-radix algorithm based on the decimation-in-time decomposition. It can flexibly compute the discrete Fourier transforms of length-q*2m where q is an odd integer. In comparison with other reported algorithms, our proposed one supports a wider range of sequence lengths, achieves a reduction of arithmetic operations and requires a simple computational structure.

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Dong, Qiao-Li, and Songnian He. "Modified Projection Algorithms for Solving the Split Equality Problems." Scientific World Journal 2014 (2014): 1–7. http://dx.doi.org/10.1155/2014/328787.

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The split equality problem (SEP) has extraordinary utility and broad applicability in many areas of applied mathematics. Recently, Byrne and Moudafi (2013) proposed a CQ algorithm for solving it. In this paper, we propose a modification for the CQ algorithm, which computes the stepsize adaptively and performs an additional projection step onto two half-spaces in each iteration. We further propose a relaxation scheme for the self-adaptive projection algorithm by using projections onto half-spaces instead of those onto the original convex sets, which is much more practical. Weak convergence results for both algorithms are analyzed.

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Bricen͂o-Arias, Luis M., and Fernando Roldán. "Split-Douglas--Rachford Algorithm for Composite Monotone Inclusions and Split-ADMM." SIAM Journal on Optimization 31, no. 4 (2021): 2987–3013. http://dx.doi.org/10.1137/21m1395144.

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Nwawuru, Francis O. "Approximation of Solutions of Split Monotone Variational Inclusion Problems and Fixed Point Problems." Pan-American Journal of Mathematics 2 (January 9, 2023): 1. http://dx.doi.org/10.28919/cpr-pajm/2-1.

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Many researchers have incorporated an inertial term and will continue to involve it in iterative algorithms due to the fact that it speeds up the rate of convergence which is desirable in applications. In this paper, we propose a new inertial extrapolation algorithm for solving split monotone variational inclusion problems which turns out to solve fixed point problems in the framework of real Hilbert spaces. Our proposed algorithm which is the generalization of split feasibility problems among many others, does not involve the knowledge of operator norm which is sometimes difficult in practice. Furthermore, we prove under some mild assumptions that the sequence generated recursively by our algorithm converges strongly to a common solution of split monotone variational inclusion problems and fixed point of κ-demicontractive mapping. Finally, we apply our algorithm to solve other related problems, precisely linear inverse problems. Some numerical illustrations are provided to further demonstrate the efficiency and competitiveness of our algorithm.

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GARCÍA, PEDRO, DAMIÁN LÓPEZ, and MANUEL VÁZQUEZ DE PARGA. "EFFICIENT DETERMINISTIC FINITE AUTOMATA SPLIT-MINIMIZATION DERIVED FROM BRZOZOWSKI'S ALGORITHM." International Journal of Foundations of Computer Science 25, no. 06 (2014): 679–96. http://dx.doi.org/10.1142/s0129054114500282.

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Minimization of deterministic finite automata is a classic problem in Computer Science which is still studied nowadays. In this paper, we relate the different split-minimization methods proposed to date, or to be proposed, and the algorithm due to Brzozowski which has been usually set aside in any classification of DFA minimization algorithms. In our work, we first propose a polynomial minimization method derived from a paper by Champarnaud et al. We also show how the consideration of some efficiency improvements on this algorithm lead to obtain an algorithm similar to Hopcroft's classic algorithm. The results obtained lead us to propose a characterization of the set of possible splitters.

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Tang, Yu-Chao, Ji-Gen Peng, and Li-Wei Liu. "A CYCLIC ALGORITHM FOR THE SPLIT COMMON FIXED POINT PROBLEM OF DEMICONTRACTIVE MAPPINGS IN HILBERT SPACES." Mathematical Modelling and Analysis 17, no. 4 (2012): 457–66. http://dx.doi.org/10.3846/13926292.2012.706236.

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The split common fixed point problem has been investigated recently, which is a generalization of the split feasibility problem and of the convex feasibility problem. We construct a cyclic algorithm to approximate a solution of the split common fixed point problem for the demicontractive mappings in a Hilbert space. Our results improve and extend previously discussed related problems and algorithms.

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ADAMU, ABUBAKAR, and AISHA A. ADAM. "Approximation of solutions of split equality fixed point problems with applications." Carpathian Journal of Mathematics 37, no. 3 (2021): 381–92. http://dx.doi.org/10.37193/cjm.2021.03.02.

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In this paper, we introduce and study an inertial algorithm for approximating solutions of split equality fixed point problem (SEFPP), involving quasi-phi-nonexpansive mappings in uniformly smooth and 2-uniformly convex real Banach spaces and establish a strong convergence theorem. We give applications of our result to split equality problem (SEP), split equality variational inclusion problem (SEVIP) and split equality equilibrium problem (SEEP). Our results extend, generalize and unify several recent inertial-type algorithms for approximating solutions of SEP and SEVIP. Moreover, to the best of our knowledge, our propose method which does not require any compactness type assumption on the operators is the first inertial algorithm for approximating solutions of SEFPP, SEP, SEVIP and SEEP in Banach spaces.

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Nandal, Ashish, Renu Chugh, and Mihai Postolache. "Iteration Process for Fixed Point Problems and Zeros of Maximal Monotone Operators." Symmetry 11, no. 5 (2019): 655. http://dx.doi.org/10.3390/sym11050655.

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We introduce an iterative algorithm which converges strongly to a common element of fixed point sets of nonexpansive mappings and sets of zeros of maximal monotone mappings. Our iterative method is quite general and includes a large number of iterative methods considered in recent literature as special cases. In particular, we apply our algorithm to solve a general system of variational inequalities, convex feasibility problem, zero point problem of inverse strongly monotone and maximal monotone mappings, split common null point problem, split feasibility problem, split monotone variational inclusion problem and split variational inequality problem. Under relaxed conditions on the parameters, we derive some algorithms and strong convergence results to solve these problems. Our results improve and generalize several known results in the recent literature.

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Ueda, Naonori, Ryohei Nakano, Zoubin Ghahramani, and Geoffrey E. Hinton. "SMEM Algorithm for Mixture Models." Neural Computation 12, no. 9 (2000): 2109–28. http://dx.doi.org/10.1162/089976600300015088.

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We present a split-and-merge expectation-maximization (SMEM) algorithm to overcome the local maxima problem in parameter estimation of finite mixture models. In the case of mixture models, local maxima often involve having too many components of a mixture model in one part of the space and too few in another, widely separated part of the space. To escape from such configurations, we repeatedly perform simultaneous split-and-merge operations using a new criterion for efficiently selecting the split-and-merge candidates. We apply the proposed algorithm to the training of gaussian mixtures and mixtures of factor analyzers using synthetic and real data and show the effectiveness of using the split- and-merge operations to improve the likelihood of both the training data and of held-out test data. We also show the practical usefulness of the proposed algorithm by applying it to image compression and pattern recognition problems.

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Dong, Qiao-Li, and Songnian He. "On Two Projection Algorithms for the Multiple-Sets Split Feasibility Problem." Journal of Applied Mathematics 2013 (2013): 1–5. http://dx.doi.org/10.1155/2013/347401.

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We present a projection algorithm which modifies the method proposed by Censor and Elfving (1994) and also introduce a self-adaptive algorithm for the multiple-sets split feasibility problem (MSFP). The global rates of convergence are firstly investigated and the sequences generated by two algorithms are proved to converge to a solution of the MSFP. The efficiency of the proposed algorithms is illustrated by some numerical tests.

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Dos Santos Marinho, Luis Fernando, Kedson Alves Silva, and Tanilson Dias dos Santos. "B2-EPG Split." Academic Journal on Computing, Engineering and Applied Mathematics 4, no. 1 (2022): 1–7. http://dx.doi.org/10.20873/uft.2675-3588.2023.v4n1.p1-7.

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On this research we study EPG graphs, in particular, we are interested on investigate the intersection between split and B2-EPGgraph classes. The results found in the literature regarding split graphs only concern about characterization in B1-EPG, that despite bringing some graphs that belong to this class, the bend number of split graphs it is still unknown. We study the split graphs whose degree of vertices on independent set is less than 2. In this work we manipulate bipartite graphs and we present representation for some bipartite graphs in B2-EPG. We build an algorithm that create a Split B2-EPG representation, also we present another algorithm that builds a representation on a grid Qw×2y+1 for any Split graph, and other results.

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Dang, Yazheng, and Yan Gao. "Inertial Iteration for Split Common Fixed-Point Problem for Quasi-Nonexpansive Operators." Abstract and Applied Analysis 2013 (2013): 1–5. http://dx.doi.org/10.1155/2013/386930.

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Inspired by the note on split common fixed-point problem for quasi-nonexpansive operators presented by Moudafi (2011), based on the very recent work by Dang et al. (2012), in this paper, we propose an inertial iterative algorithm for solving the split common fixed-point problem for quasi-nonexpansive operators in the Hilbert space. We also prove the asymptotical convergence of the algorithm under some suitable conditions. The results improve and develop previously discussed feasibility problems and related algorithms.

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., M. Tamilselvi. "RESOURCEFUL FAST DHT ALGORITHM FOR VLSIIMPLEMENTATION BY SPLIT RADIX ALGORITHM." International Journal of Research in Engineering and Technology 03, no. 14 (2014): 44–48. http://dx.doi.org/10.15623/ijret.2014.0314009.

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Rajappa, Gautham Puttur, Joseph H. Wilck, and John E. Bell. "An Ant Colony Optimization and Hybrid Metaheuristics Algorithm to Solve the Split Delivery Vehicle Routing Problem." International Journal of Applied Industrial Engineering 3, no. 1 (2016): 55–73. http://dx.doi.org/10.4018/ijaie.2016010104.

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Split Delivery Vehicle Routing Problem (SDVRP) is a relaxation of the Capacitated Vehicle Routing Problem (CVRP) that allows the same customer to be served by more than one vehicle. Existing literature has applied Ant Colony Optimization (ACO) and Genetic Algorithm (GA) to other variants of VRP but no known research effort has applied ACO or a combination of ACO and GA to solve the Split Delivery Vehicle Routing Problem (SDVRP). Hence, two algorithms using ACO and hybrid metaheuristics algorithm comprising a combination of ACO, Genetic Algorithm (GA) and heuristics is proposed and tested on existing benchmark SDVRP problems. The results indicate that the two proposed algorithms are competitive in both solution quality and solution time and for some problem instances, the best ever solutions have been found.

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