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Journal articles on the topic 'Weight comparison algorithm'

Author: Grafiati

Published: 3 June 2025

Last updated: 31 July 2025

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1

Evans, Richard, Jennifer Burns, Laura Damschroder, et al. "Deriving Weight From Big Data: Comparison of Body Weight Measurement–Cleaning Algorithms." JMIR Medical Informatics 10, no. 3 (2022): e30328. http://dx.doi.org/10.2196/30328.

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Background Patient body weight is a frequently used measure in biomedical studies, yet there are no standard methods for processing and cleaning weight data. Conflicting documentation on constructing body weight measurements presents challenges for research and program evaluation. Objective In this study, we aim to describe and compare methods for extracting and cleaning weight data from electronic health record databases to develop guidelines for standardized approaches that promote reproducibility. Methods We conducted a systematic review of studies published from 2008 to 2018 that used Vete

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Sarvade, Akanksha. "Analysis between Prims and Kruskal’s Algorithm." International Journal for Research in Applied Science and Engineering Technology 12, no. 11 (2024): 2464–67. https://doi.org/10.22214/ijraset.2024.65593.

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The project is an analytical comparison between two algorithms that is Prim’s algorithm and Kruskal’s algorithm in MST (minimum spanning tree). Both the algorithms aim to connect all the vertices based on their weight but differ in implementation and approach. Prim’s algorithm is Greedy algorithm which makes the minimum spanning tree according to their incremental weight It starts with one vertex and expands its MST, it always selects smallest edge in MST. Kruskal’s algorithm is also greedy algorithm but its approaches differently. It starts with all the vertices and no edge and it adds edge w

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Austrow, J. C. "An Optimum Balance Weight Search Algorithm." Journal of Engineering for Gas Turbines and Power 116, no. 3 (1994): 678–81. http://dx.doi.org/10.1115/1.2906873.

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A mathematical description for an optimum balance weight search algorithm for single-plane multipoint balance is presented. The algorithm uses influence coefficients, either measured or known beforehand, and measured complex vibration data to determine an optimum balance correction weight. The solution minimizes the maximum residual vibration. The algorithm allows user-defined balance weights to be analyzed and evaluated. A test case is presented showing actual results and comparison with a least-squares solution algorithm. An efficient multiplane influence coefficient calculation scheme is al

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Zhang, Rener. "The comparison of three MST algorithms." Applied and Computational Engineering 17, no. 1 (2023): 191–97. http://dx.doi.org/10.54254/2755-2721/17/20230939.

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The minimum spanning tree, connecting all the nodes of a connected, weighted graph with the minimum possible total edge weight, is a fundamental concept of graph theory. Thus, how to find the minimum spanning tree (MST) with higher efficiency appears to be crucial. Three kinds of algorithms for this problem have already been developed: Kruskal, Prim, Boruvka. In order to make readers have a better understanding of the three algorithms in the process of studying and teaching, this paper uses the method of comparing to indicate the differences and commonalities between these three algorithms, dr

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Lee, Seungjae, Junhong Ha, Sudeok Shon, and Donwoo Lee. "Weight Optimization of Discrete Truss Structures Using Quantum-Based HS Algorithm." Buildings 13, no. 9 (2023): 2132. http://dx.doi.org/10.3390/buildings13092132.

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Recently, a new field that combines metaheuristic algorithms and quantum computing has been created and is being applied to optimization problems in various fields. However, the application of quantum computing-based metaheuristic algorithms to the optimization of structural engineering is insufficient. Therefore, in this paper, we tried to optimize the weight of the truss structure using the QbHS (quantum-based harmony search) algorithm, which combines quantum computing and conventional HS (harmony search) algorithms. First, the convergence performance according to the parameter change of the

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Baş, Emine, and Lütfi Batuhan Güner. "Weight Optimization of Oil Type Transformer with Crayfish Optimization Algorithm." Sinop Üniversitesi Fen Bilimleri Dergisi 10, no. 1 (2025): 1–28. https://doi.org/10.33484/sinopfbd.1511204.

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Transformers used in the transmission and distribution of electricity are electrical machines that ensure the transmission of electricity at constant power and frequency by using magnetic field strength. In this study, weight optimization of oil-type power and distribution-type transformers in different power levels (50kVA and 100kVA) was calculated using the Crayfish Optimization Algorithm (COA). The purpose of the study is to perform weight optimization and calculate weight reduction. The variable parameters used as current density value (s) and iron section suitability value (C) were determ

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Yu, Guolong, Yong Zhao, Zhongwei Cui, and Zuo Yu. "A QPSO algorithm based on hierarchical weight and its application in cloud computing task scheduling." Computer Science and Information Systems, no. 00 (2020): 33. http://dx.doi.org/10.2298/csis200223033y.

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The computing method of the average optimal position is one of the most important factors that affect the optimization performance of the QPSO algorithm. Therefore, a particle position weight computing method based on particle fitness value grading is proposed, which is called HWQPSO (hierarchical weight QPSO). In this method, the higher the fitness value of a particle, the higher the level of the particle, and the greater the weight. Particles at different levels have different weights, while particles at the same level have the same weight. Through this method, the excellent particles have h

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Memarian, Taher, and Yaser Shahbazi. "Integrated Metaheuristic Differential Evolution Optimization Algorithm and Pseudo Static Analysis of Concrete Gravity Dam." Civil Engineering Journal 3, no. 8 (2017): 617–25. http://dx.doi.org/10.28991/cej-2017-00000116.

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A differential evolution-algorithm-based optimum design method is presented for concrete gravity dams under stability, principal stress, and sliding constraints. A gravity dam is a large scale hydraulic structure providing its stability based on weight of concrete volume. Hence, optimization of dam cross-section leads to an economic and low cost structure. For this aim, a general dam section is reconstructed with seven proper horizontal and vertical geometric parameters which take into account all possible cross section shapes. Weight of dam is considered as goal function and the optimization

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Gonzalez, Luciano A., Jillian E. M. Burgess, and Milad Bagheri Shirvan. "267 Comparison of methods to process remotely collected body weight in feedlot steers." Journal of Animal Science 102, Supplement_3 (2024): 92. http://dx.doi.org/10.1093/jas/skae234.105.

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Abstract New technologies such as automatic in-pen weighing of cattle offer great opportunities to monitor, improve and control livestock production. The large amount of raw BW data recorded must be processed to estimate BW minimizing the impact of erroneous records and the large variability due to various factors such as fill of the gastrointestinal tract. The objective of the present study was to compare two data processing methods of remotely collected body weight (BW) in feedlot steers against traditional weighing measured in central handling facilities. The BW data were collected from a s

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Bhowmik, B., and Chowdhury S. Nag. "Prograph Based Analysis of Single Source Shortest Path Problem with Few Distinct Positive Lengths." Engineering, Technology & Applied Science Research 1, no. 4 (2011): 90–97. https://doi.org/10.5281/zenodo.14029.

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In this paper we propose an experimental study model S3P2 of a fast fully dynamic programming algorithm design technique in finite directed graphs with few distinct nonnegative real edge weights. The Bellman-Ford’s approach for shortest path problems has come out in various implementations. In this paper the approach once again is re-investigated with adjacency matrix selection in associate least running time. The model tests proposed algorithm against arbitrarily but positive valued weighted digraphs introducing notion of  Prograph that speeds up finding the shortest path over prev

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Wu, Xi, Mingyuan Xie, Wei Wu, and Jiliu Zhou. "Nonlocal Mean Image Denoising Using Anisotropic Structure Tensor." Advances in Optical Technologies 2013 (February 12, 2013): 1–6. http://dx.doi.org/10.1155/2013/794728.

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We present a novel nonlocal mean (NLM) algorithm using an anisotropic structure tensor to achieve higher accuracy of imaging denoising and better preservation of fine image details. Instead of using the intensity to identify the pixel, the proposed algorithm uses the structure tensor to characterize the boundary information around the pixel more comprehensively. Meanwhile, similarity of the structure tensor is computed in a Riemannian space for more rigorous comparison, and the similarity weight of the pixel (or patch) is determined by the intensity and structure tensor simultaneously. The pro

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Yu, Xinyi. "Analysis and comparison of two classical greedy algorithms for minimum spanning tree." Theoretical and Natural Science 5, no. 1 (2023): 700–704. http://dx.doi.org/10.54254/2753-8818/5/20230464.

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The total weight of the minimum spanning is the smallest in the connected graph. It can be used to solve many practical problems in urban life. Prims algorithm and Kruskals algorithm are greedy algorithms for solving the minimum spanning tree problem. But they make greedy choices in different ways. The paper focuses on two greedy algorithms for solving the minimum spanning tree problem. The author will evaluate each algorithms complexity and determine their most suitable condition as well. The author compares the running process of the two algorithms and analyzes the relationship between their

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Feng, Ningning, Xi Kang, Haoyuan Han, Gang Liu, Yan’e Zhang, and Shuli Mei. "Research on a Dynamic Algorithm for Cow Weighing Based on an SVM and Empirical Wavelet Transform." Sensors 20, no. 18 (2020): 5363. http://dx.doi.org/10.3390/s20185363.

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Weight is an important indicator of the growth and development of dairy cows. The traditional static weighing methods require considerable human and financial resources, and the existing dynamic weighing algorithms do not consider the influence of the cow motion state on the weight curve. In this paper, a dynamic weighing algorithm for cows based on a support vector machine (SVM) and empirical wavelet transform (EWT) is proposed for classification and analysis. First, the dynamic weight curve is obtained by using a weighing device placed along a cow travel corridor. Next, the data are preproce

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Haibo, MENG, YU Haiyan, CHEN Xiushuang, Han Canfeng, Chen Lei, and YU Zhiting. "COMPARISON OF GENETIC ALGORITHM OPERATORS IN WEIGHT OPTIMIZATION OF CONDENSERS." Proceedings of the International Conference on Nuclear Engineering (ICONE) 2019.27 (2019): 1737. http://dx.doi.org/10.1299/jsmeicone.2019.27.1737.

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Abderazek, Hammoudi, Ferhat Hamza, Ali Riza Yildiz, and Sadiq M. Sait. "Comparative investigation of the moth-flame algorithm and whale optimization algorithm for optimal spur gear design." Materials Testing 63, no. 3 (2021): 266–71. http://dx.doi.org/10.1515/mt-2020-0039.

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Abstract In this study, two recent algorithms, the whale optimization algorithm and moth-flame optimization, are used to optimize spur gear design. The objective function is the minimization of the total weight of the spur gear pair. Moreover, the optimization problem is subjected to constraints on the main kinematic and geometric conditions as well as to the resistance of the material of the gear system. The comparison between moth-flame optimization (MFO), the whale optimization algorithm (WOA), and previous studies indicate that the final results obtained from both algorithms lead to a redu

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Tilahun, Surafel Luleseged, and Maba B. Matadi. "Weight Minimization of a Speed Reducer Using Prey Predator Algorithm." International Journal of Manufacturing, Materials, and Mechanical Engineering 8, no. 2 (2018): 19–32. http://dx.doi.org/10.4018/ijmmme.2018040102.

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This article describes how a speed reducer is a mechanical device which is very useful to reduce speed in different machineries. The use of gears to adjust a speed is an old practice, however the formulation of the problem as an optimization problem and solving it using different approaches begun in early 1970's. The problem is a constrained, nonlinear and nonconvex problem. That makes it challenging to handle it by deterministic approaches. Hence, different metaheuristic and hybrid methods have been proposed and used. Furthermore, due to the challenging behaviour of the problem, it has been u

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Wang, Guan, Yuxin Wang, Hui Liu, and He Guo. "HSIP: A Novel Task Scheduling Algorithm for Heterogeneous Computing." Scientific Programming 2016 (2016): 1–11. http://dx.doi.org/10.1155/2016/3676149.

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High-performance heterogeneous computing systems are achieved by the use of efficient application scheduling algorithms. However, most of the current algorithms have low efficiency in scheduling. Aiming at solving this problem, we propose a novel task scheduling algorithm for heterogeneous computing named HSIP (heterogeneous scheduling algorithm with improved task priority) whose functionality relies on three pillars: (1) an improved task priority strategy based on standard deviation with improved magnitude as computation weight and communication cost weight to make scheduling priority more re

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18

Sarbaini, Sarbaini, and Ilham Dangu Rianjaya. "MENENTUKAN JALUR TERPENDEK MENGGUNAKAN ALGORITMA A* DAN ALGORITMA FLOYD WARSHAL." MAp (Mathematics and Applications) Journal 5, no. 1 (2023): 34–47. https://doi.org/10.15548/map.v5i1.5781.

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When graphs are used to solve the problem of determining the shortest route, it has become a common topic of discussion. Typically, these solutions are used to optimize aspects such as travel time. Using the Floyd-Warshall and A* algorithms, this research assists the community, particularly visitors, in determining the most sensible route from the Rimbo Panjang front gate to each building at UIN Suska Riau. The calculation technique is performed manually. The algorithm developed by Floyd Warshall yields more efficient calculation results. The results of calculations conducted by both algorithm

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Yu, Hongli, Yuelin Gao, Le Wang, and Jiangtao Meng. "A Hybrid Particle Swarm Optimization Algorithm Enhanced with Nonlinear Inertial Weight and Gaussian Mutation for Job Shop Scheduling Problems." Mathematics 8, no. 8 (2020): 1355. http://dx.doi.org/10.3390/math8081355.

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Job shop scheduling problem (JSSP) has high theoretical and practical significance in academia and manufacturing respectively. Therefore, scholars in many different fields have been attracted to study this problem, and many meta-heuristic algorithms have been proposed to solve this problem. As a meta-heuristic algorithm, particle swarm optimization (PSO) has been used to optimize many practical problems in industrial manufacturing. This paper proposes a hybrid PSO enhanced with nonlinear inertia weight and and Gaussian mutation (NGPSO) to solve JSSP. Nonlinear inertia weight improves local sea

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Şengül, Turgay, Şenol Çelik, Ahmet Yusuf Şengül, Hakan İnci, and Ömer Şengül. "Investigation of growth curves with different nonlinear models and MARS algorithm in broiler chickens." PLOS ONE 19, no. 11 (2024): e0307037. http://dx.doi.org/10.1371/journal.pone.0307037.

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This study was conducted to determine the live weight model of the broiler chicks by using the most appropriate mathematical growth curves. Live weights were used in broiler chicks grown for 0–6 weeks. Logistics, Gompertz, Weibull, Hossfeld and Von Bertalanffy models and multivariate adaptive regression splines (MARS) data mining algorithm were used to define the live weights of the chickens. In the comparison of the models, the determination coefficient (R2), mean square error (MSE), Akaike’s Information Criterion (AIC) and Schwarz Bayesian Information Criterion (BIC) values were used. As a r

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Eker, Erdal, Murat Kayri, Serdar Ekinci, and Davut İzci. "Comparison of Swarm-based Metaheuristic and Gradient Descent-based Algorithms in Artificial Neural Network Training." ADCAIJ: Advances in Distributed Computing and Artificial Intelligence Journal 12, no. 1 (2023): e29969. http://dx.doi.org/10.14201/adcaij.29969.

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This paper aims to compare the gradient descent-based algorithms under classical training model and swarm-based metaheuristic algorithms in feed forward backpropagation artificial neural network training. Batch weight and bias rule, Bayesian regularization, cyclical weight and bias rule and Levenberg-Marquardt algorithms are used as the classical gradient descent-based algorithms. In terms of the swarm-based metaheuristic algorithms, hunger games search, gray wolf optimizer, Archimedes optimization, and the Aquila optimizer are adopted. The Iris data set is used in this paper for the training.

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Zeng, Yu, and Xing Xu. "The Construction and Optimization of an AI Education Evaluation Indicator Based on Intelligent Algorithms." International Journal of Cognitive Informatics and Natural Intelligence 16, no. 1 (2022): 1–22. http://dx.doi.org/10.4018/ijcini.315275.

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The basic tool in the analytic hierarchy process (AHP) is the complete judgment matrix. To address the weakness of the AHP in determining weight in the comprehensive evaluation system, the particle swarm optimization (PSO)-AHP model proposed in this paper is based on the PSO in the meta-heuristic algorithm. The model was used to solve the indicator weights in the evaluation system of AI education in primary and secondary schools in Fujian Province and was compared with the genetic algorithm and war strategy optimization algorithm. From the comparison results, the PSO-AHP optimization is more e

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Bremner, Alexander, Li Yen Chan, Courtney Jones, and Shaheen P. Shah. "Comparison of Weight-Gain-Based Prediction Models for Retinopathy of Prematurity in an Australian Population." Journal of Ophthalmology 2023 (August 17, 2023): 1–8. http://dx.doi.org/10.1155/2023/8406287.

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Purpose. Four weight-gain-based algorithms are compared for the prediction of type 1 ROP in an Australian cohort: the weight, insulin-like growth factor, neonatal retinopathy of prematurity (WINROP) algorithm, the Children’s Hospital of Philadelphia Retinopathy of Prematurity (CHOPROP), the Colorado Retinopathy of Prematurity (CO-ROP) algorithm, and the postnatal growth, retinopathy of prematurity (G-ROP) algorithm. Methods. A four-year retrospective cohort analysis of infants screened for ROP in a tertiary neonatal intensive care unit in Brisbane, Australia. The main outcome measures were sen

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FIORI, SIMONE. "A MINOR SUBSPACE ALGORITHM BASED ON NEURAL STIEFEL DYNAMICS." International Journal of Neural Systems 12, no. 05 (2002): 339–50. http://dx.doi.org/10.1142/s0129065702001217.

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In the present paper we investigate iterative minor subspace analysis computation by describing a neural approach based on weight flow on Stiefel manifold and by discussing four neural algorithms and a purely algebraic algorithm known from the scientific literature. A comparison of numerical experimental results and computational complexity estimates confirms the effectiveness and efficiency of the proposed approach.

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Ulfah, Sofia. "COMPARISON OF C4.5 ALGORITHM WITH THE NAVE BAYES CLASSIFIER ALGORITHM FOR CLASSIFICATION OF NUTRITIONAL STATUS OF TOODLER." Jurnal DISPROTEK 13, no. 1 (2022): 1–10. http://dx.doi.org/10.34001/jdpt.v13i1.3044.

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So far, Body Mass Index (BMI) is used as a measuring tool to assess a person's nutritional status. If there are two who have the same weight and height, they may have different nutritional status. Anthropometric measuring tools play a very important role in determining the nutritional status. The anthropometric guidelines for determining nutritional status are the parameters chosen and recommended, which include an assessment of age, weight, body length or height. On the other hand, technological developments are currently increasing and giving a great influence in almost every sector of life

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Sampurno, Global Ilham, Endang Sugiharti, and Alamsyah Alamsyah. "Comparison of Dynamic Programming Algorithm and Greedy Algorithm on Integer Knapsack Problem in Freight Transportation." Scientific Journal of Informatics 5, no. 1 (2018): 49. http://dx.doi.org/10.15294/sji.v5i1.13360.

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At this time the delivery of goods to be familiar because the use of delivery of goods services greatly facilitate customers. PT Post Indonesia is one of the delivery of goods. On the delivery of goods, we often encounter the selection of goods which entered first into the transportation and held from the delivery. At the time of the selection, there are Knapsack problems that require optimal selection of solutions. Knapsack is a place used as a means of storing or inserting an object. The purpose of this research is to know how to get optimal solution result in solving Integer Knapsack proble

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Riti, Yosefina Finsensia, Jonathan Steven Iskandar, and Hendra Hendra. "Comparison Analysis of Graph Theory Algorithms for Shortest Path Problem." Jurnal Sisfokom (Sistem Informasi dan Komputer) 12, no. 3 (2023): 415–24. http://dx.doi.org/10.32736/sisfokom.v12i3.1756.

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The Sumba region, Indonesia, is known for its extraordinary natural beauty and unique cultural richness. There are 19 interesting tourist attractions spread throughout the area, but tourists often face difficulties in planning efficient visiting routes. From this case, it can be solved by applying graph theory in terms of searching for the shortest distance which is completed using the shortest path search algorithm. Then these 19 tourist objects are used to build a weighted graph, where the nodes represent the tourist objects and the edges of the graph describe the distance or travel time bet

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Zhang, Xiushan. "Intelligent Recommendation Algorithm of Multimedia English Distance Education Resources Based on User Model." Journal of Mathematics 2022 (January 13, 2022): 1–8. http://dx.doi.org/10.1155/2022/2012700.

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Based on the understanding and comparison of various main recommendation algorithms, this paper focuses on the collaborative filtering algorithm and proposes a collaborative filtering recommendation algorithm with improved user model. Firstly, the algorithm considers the score difference caused by different user scoring habits when expressing preferences and adopts the decoupling normalization method to normalize the user scoring data; secondly, considering the forgetting shift of user interest with time, the forgetting function is used to simulate the forgetting law of score, and the weight o

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Suo, Dongnan. "Optimization of CSO algorithm based on adaptive inertia weight coefficient." Journal of Physics: Conference Series 2078, no. 1 (2021): 012009. http://dx.doi.org/10.1088/1742-6596/2078/1/012009.

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Abstract The traditional CSO algorithm is easy to fall into local extremum in optimization. In this paper, a CSO algorithm based on weight coefficient is proposed. In the CSO algorithm, the inertia weight coefficient is introduced into the hen position formula, and the learning factor influenced by the rooster is added to the chick position formula. Finally, using the idea of heredity, individuals with excellent fitness value are selected for crossover and mutation with a certain probability. Through the simulation comparison of five typical test functions, the simulation results show that the

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Abed, Mustafa Salah, Omar Farouq Lutfy, and Qusay Fadhel Al-Doori. "Adaptive weight grey wolf algorithm application on path planning in unknown environments." Indonesian Journal of Electrical Engineering and Computer Science 27, no. 3 (2022): 1375. http://dx.doi.org/10.11591/ijeecs.v27.i3.pp1375-1387.

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Autonomous mobile robots developed using metaheuristic algorithms are increasingly becoming a hot topic in control and computer sciences. Specifically, finding the shortest route to the goal and avoiding hurdles are current subjects of autonomous mobile robots. The Modified Grey Wolf Optimization (MGWO) is demonstrated in this work using two approaches: first, the Adaptive Adjustment Approach of the Control Parameters, and second, the Adaptive Variable Weights method. Those two methods are utilized for updating the wolf position, accelerate convergence, and cut down on time. The proposed onlin

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Abed, Mustafa Salah, Omar Farouq Lutfy, and Qusay Fadhel Al-Doori. "Adaptive weight grey wolf algorithm application on path planning in unknown environments." Indonesian Journal of Electrical Engineering and Computer Science 27, no. 3 (2022): 1375–87. https://doi.org/10.11591/ijeecs.v27.i3.pp1375-1387.

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Autonomous mobile robots developed using metaheuristic algorithms are increasingly becoming a hot topic in control and computer sciences. Specifically, finding the shortest route to the goal and avoiding hurdles are current subjects of autonomous mobile robots. The modified grey wolf optimization (MGWO) is demonstrated in this work using two approaches: first, the adaptive adjustment approach of the control parameters, and second, the adaptive variable weights method. Those two methods are utilized for updating the wolf position, accelerate convergence, and cut down on time. The proposed onlin

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K.S., Sree Ranjini. "A study on performance of MHDA in training MLPs." Engineering Computations 36, no. 6 (2019): 1820–34. http://dx.doi.org/10.1108/ec-05-2018-0216.

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Purpose In recent years, the application of metaheuristics in training neural network models has gained significance due to the drawbacks of deterministic algorithms. This paper aims to propose the use of a recently developed “memory based hybrid dragonfly algorithm” (MHDA) for training multi-layer perceptron (MLP) model by finding the optimal set of weight and biases. Design/methodology/approach The efficiency of MHDA in training MLPs is evaluated by applying it to classification and approximation benchmark data sets. Performance comparison between MHDA and other training algorithms is carrie

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Crismayella, Yuveinsiana, Neva Satyahadewi, and Hendra Perdana. "Comparison of Adaboost Application to C4.5 and C5.0 Algorithms in Student Graduation Classification." Pattimura International Journal of Mathematics (PIJMath) 2, no. 1 (2023): 07–16. http://dx.doi.org/10.30598/pijmathvol2iss1pp07-16.

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Students become a benchmark used to assess quality and evaluate college learning plans. Therefore, students who graduate not on time can have an effect on accreditation assessment. The characteristics of students who graduate on time or not on time in determining student graduation can be analyzed using classification techniques in data mining, namely the C4.5 and C5.0 algorithms. The purpose of this study is to compare the application of the Adaboost Algorithm to the C4.5 and C5.0 Algorithms in the classification of student graduation. The data used is the graduation data of students of the S

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Feng, Yuan, Li Xia, Li Ming Wang, Le Ping Bu, and Ying Shao. "Loading Priority Evaluation Based on PRISM Classifier." Advanced Materials Research 301-303 (July 2011): 768–73. http://dx.doi.org/10.4028/www.scientific.net/amr.301-303.768.

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Loading management is one of the most important technologies for ship power system. Reasonable distribution of electric energy to the loading can achieve the goal of optimal energy schedule and its primary issue is to make a reasonable loading priority evaluation. This paper analyzed the shortcomings of the loading priority evaluation using the AHP and proposed a kind of algorithm of property weight evaluation based on PRISM classification, effectively combing expertise and characteristics of the objective data itself together. The results show that: the loading priority of ship power system i

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Puleio, A., L. Martellucci, R. Rossi, N. Rutigliano, I. Wyss, and P. Gaudio. "An alternative SNR-based weighted-LSM algorithm to classify and measure the concentration of Biological Agents from Laser-Induced Fluorescence." Journal of Instrumentation 18, no. 05 (2023): C05004. http://dx.doi.org/10.1088/1748-0221/18/05/c05004.

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Abstract Optical spectroscopic techniques, such as Laser-Induced Breakdown Spectroscopy (LIBS) or Laser-Induced Fluorescence (LIF), have already been used to study and detect Biological Agents (BAs). Unfortunately, BAs usually share similar-shaped emitted spectra and low-signal intensities, making their detection and classification difficult to assess. Least-Square Minimisation (LSM) based algorithms are usually deployed to measure the concentration of agents from spectra. Recently, it has been shown how the use of ad hoc weights can help in improving the performance of the concentration evalu

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V.P., Sakthivel. "NEW PARTICLE SWARM OPTIMIZER WITH NATURE INSPIRED DYNAMIC INERTIA WEIGHT FOR ECONOMIC POWER DISPATCH." GLOBAL JOURNAL OF ENGINEERING SCIENCE AND RESEARCHES 5, no. 2 (2019): 104–11. https://doi.org/10.5281/zenodo.2653662.

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This paper presents a new particle swarm optimization based on nature inspired dynamic inertia weight (PSO-NIDIW) for solving economic power dispatch problems. NIDIW which mimics the social behavior of humans is proposed to cogently balance the global exploration and local exploitation abilities for PSO. In each iteration during the run, each particle can select appropriate weight according to its situation. The performance of the PSO algorithm is improved by this fine strategy of naturally adjusting dynamic inertia weight. The economic load dispatch (ELD) is formulated as a nonlinear constrai

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Wang, Shangfei. "Isolation Forest Anomaly Detection Algorithm Based On Multi-level Sub-subspace Partition." International Journal of Computer Science and Information Technology 4, no. 2 (2024): 149–59. http://dx.doi.org/10.62051/ijcsit.v4n2.20.

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In the research of credit loan fraud detection, the isolation forest algorithm has attracted much attention because of its ability to efficiently process large-scale data sets. However, when facing high-dimensional data, the performance of the isolation forest algorithm is easily affected, resulting in deviation of the detection results. In order to solve the above problems, this paper proposes an isolation forest anomaly detection algorithm based on multi-level sub-subspace division. Firstly, the random forest algorithm is used to evaluate the importance of each feature, and the data is divid

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Liu, Yaoyao, Ping Guo, and Yi Zeng. "HA-CCP: A Hybrid Algorithm for Solving Capacitated Clustering Problem." Computational Intelligence and Neuroscience 2022 (January 21, 2022): 1–24. http://dx.doi.org/10.1155/2022/6400318.

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The capacitated clustering problem (CCP) divides the vertices of the undirected graph into several disjoint clusters so that the sum of the node weights in each cluster meets the capacity limit while maximizing the sum of the weight of the edges between nodes in the same cluster. CCP is a typical NP-hard problem with a wide range of engineering applications. In recent years, heuristic algorithms represented by greedy random adaptive search program (GRASP) and variable neighborhood search (VNS) have achieved excellent results in solving CCP. To improve the efficiency and quality of the CCP solu

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Deng, Zhong Liang, and Dan Dan Shi. "An Identification Algorithm of Insects Wing Based on Grid." Applied Mechanics and Materials 80-81 (July 2011): 1232–36. http://dx.doi.org/10.4028/www.scientific.net/amm.80-81.1232.

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In order to identify and classify insects wing, a new identification algorithms of insects wing was presented in this paper. Wing image was divided into several grids in this algorithm, and according to the importance of the wing features based on every grid, targeted to set the weight for each grid and calculate the final similar, the result of comparison of wing features will be more comprehensive and accurate. Experimental results show that the proposed algorithm will be more accurate to compare wing features, and then identify the insect species.

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Shin, Donghee. "A Cross-National Study on the Perception of Algorithm News in the East and the West." Journal of Global Information Management 29, no. 2 (2021): 77–101. http://dx.doi.org/10.4018/jgim.2021030105.

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Although algorithms have been widely used to deliver useful services, how users actually experience algorithm-driven news remains unclear. This study examines user attitude and perception of algorithmic journalism and identifies the similarities and differences in experience and satisfaction formation. A comparative study between the United States (U.S.) and South Korea was conducted to examine how the two countries' users experience the quality of algorithm-driven news services and how individuals perceive the topics of fairness, accountability, and transparency. The notable similarities and

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Wang, Chenlin, Gongzhuo Yang, Junyu Li, and Qibai Huang. "Fuzzy Adaptive PSO-ELM Algorithm Applied to Vehicle Sound Quality Prediction." Applied Sciences 13, no. 17 (2023): 9561. http://dx.doi.org/10.3390/app13179561.

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When dealing with specific tasks, the hidden layer output matrix of an extreme learning machine (ELM) may change, largely due to the random assigned weight matrix of the input layer and the threshold matrix of the hidden layer, which sequentially leads to the corresponding change to output weights. The unstable fluctuations of the output weights increase the structural risk and the empirical risk of ELM. This paper proposed a fuzzy adaptive particle swarm optimization (PSO) algorithm to solve this problem, which could nonlinearly control the inertia factor during the iteration by fuzzy control

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Islam, M. Fakhrul, Joarder Kamruzzaman, and Guojun Lu. "Improved ANN Based Tap-Changer Controller Using Modified Cascade-Correlation Algorithm." Journal of Advanced Computational Intelligence and Intelligent Informatics 9, no. 3 (2005): 226–34. http://dx.doi.org/10.20965/jaciii.2005.p0226.

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Artificial Neural Network (ANN) based tap changer control of closed primary bus and cross network connected parallel transformers has demonstrated potential use in power distribution system. In those research works the proposed ANN for application in this control were developed using various algorithms and concluded that a network trained by Bayesian Regularization (BR) backpropagation algorithm produced the best performance measured in terms of correct tap changing decisions. However, further improvement of ANN based transformer tap changer operation is always desirable. A general rule for ob

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Cahyaningtyas, Christian, Danny Manongga, and Irwan Sembiring. "ALGORITHM COMPARISON AND FEATURE SELECTION FOR CLASSIFICATION OF BROILER CHICKEN HARVEST." Jurnal Teknik Informatika (Jutif) 3, no. 6 (2022): 1717–27. http://dx.doi.org/10.20884/1.jutif.2022.3.6.493.

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Broiler chickens are the result of superior breeds that produce a lot of meat. In practice, however, many breeders experience crop failure, which has a serious impact on the economy and can also affect farmer quality, resulting in sanctions. The value of the performance index produced at harvest indicates the success rate of harvesting broiler chickens. Broiler crop yield data can be used to help classify broiler crop yield data using an approach method. The CRISP-DM (Cross Industry Standard Process for Data Mining) method was used in this study's data mining technique. This study compares 3 c

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Tan, Xiaohua, Xue Chen, Xiaopin Li, Qingyan Mei, and Zhelun Zhang. "Efficiency prediction of foam drainage measures using enhanced dung beetle optimization." Intelligent Decision Technologies 19, no. 2 (2024): 1142–57. https://doi.org/10.1177/18724981241295939.

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The dung beetle algorithm, when applied to complex multimodal function problems, tends to fall into local optima and may converge prematurely to suboptimal solutions, thereby restricting its application in high-dimensional and complex optimization issues. To address these limitations, a new dynamic weight adjustment mechanism and escape strategy have been introduced. Through the solution and comparison of 12 benchmark test functions, the improved dung beetle optimization algorithm (DGDBO) has demonstrated enhanced global search capabilities and resistance to premature convergence. This is evid

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TATAS, K., D. J. SOUDRIS, D. SIOMOS, and A. THANAILAKIS. "A NOVEL DIVISION ALGORITHM AND ARCHITECTURES FOR PARALLEL AND SEQUENTIAL PROCESSING." Journal of Circuits, Systems and Computers 14, no. 02 (2005): 281–95. http://dx.doi.org/10.1142/s0218126605002295.

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A new algorithm for reducing the division operation to a series of smaller divisions is introduced. Partitioning the dividend into segments, we perform divisions, shifts, and accumulations taking into account the weight of dividend bits. Each partial division can be performed by any existing division algorithm. From an algorithmic point of view, computation analysis is performed in comparison with the existing algorithms. From an implementation point of view, since the division can be performed by any existing divider, the designer can choose the divider which best meets his specifications. Al

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Lin, Teng Hang Li. "Modified Discrete Firefly Algorithm Combining Genetic Algorithm for Traveling Salesman Problem." TELKOMNIKA Telecommunication, Computing, Electronics and Control 16, no. 1 (2018): 424–31. https://doi.org/10.12928/TELKOMNIKA.v16i1.4752.

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The Firefly Algorithm (FA) has a few disadvantages in solving the constrained global optimization problem, including that it is difficult to produce initial population, the size of relative attractiveness has nothing to do with the absolute brightness of fireflies, the inertia weight does not take full advantage of the information of objective function, and it cannot better control and constrain the mobile distance of firefly. In this paper, we propose a novel method based on discrete firefly algorithm combining genetic algorithm for traveling salesman problem. We redefine the distance of fire

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Yücel, Melda. "Comparison of Flower Pollination Algorithm and Particle Swarm Optimization for Structural Weight Minimization of RC Beams with Carbon Fiber Reinforced Polymer (CFRP)." Afyon Kocatepe University Journal of Sciences and Engineering 25, no. 2 (2025): 381–87. https://doi.org/10.35414/akufemubid.1507994.

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In order to generate the best namely most appropriate design, different methodologies can be preferred. In nowadays, especially, metaheuristic algorithms, which have been proposed by inspiring various metaphors such as genetic, abilities of animals or natural behaviors of plants etc., can be useful, suitable and effective to provide the target results for any optimization problem. For this reason, in the current study, to design the most appropriate structural model intended for reinforced concrete (RC) beam structures supported with carbon fiber reinforced polymer (CFRP), two different popula

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Liu, Si Yuan, Yan Cheng Liu, Chuan Wang, and Jun Jie Ren. "Marine Asynchronous Propulsion Motor Parameter Identification Using Dynamic Particle Swarm Optimization." Advanced Materials Research 860-863 (December 2013): 2211–17. http://dx.doi.org/10.4028/www.scientific.net/amr.860-863.2211.

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This paper proposes a new application of dynamic particle swarm optimization (PSO) algorithm for parameter identification of vector controlled asynchronous propulsion motor (APM) in electric propulsion ship. The dynamic PSO modifies the inertia weight, learning coefficients and two independent random sequences which affect the convergence capability and solution quality, in order to improve the performance of the standard PSO algorithm. The standard PSO and dynamic PSO algorithms use measurements of the mt-axis currents, voltages of APM as the inputs to parameter identification system. The exp

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Gürses, Dildar, Sujin Bureerat, Sadiq M. Sait, and Ali Rıza Yıldız. "Comparison of the arithmetic optimization algorithm, the slime mold optimization algorithm, the marine predators algorithm, the salp swarm algorithm for real-world engineering applications." Materials Testing 63, no. 5 (2021): 448–52. http://dx.doi.org/10.1515/mt-2020-0076.

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Abstract This paper focuses on a comparision of recent algorithms such as the arithmetic optimization algorithm, the slime mold optimization algorithm, the marine predators algorithm, and the salp swarm algorithm. The slime mold algorithm (SMA) is a recent optimization algorithm. In order to strengthen its exploitation and exploration abilities, in this paper, a new hybrid slime mold algorithm-simulated annealing algorithm (HSMA-SA) has been applied to structural engineering design problems. As a result of the rules and practices that have become mandatory for fuel emissions by international o

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Gu, Yi, and Kang Li. "Entropy-Based Multiview Data Clustering Analysis in the Era of Industry 4.0." Wireless Communications and Mobile Computing 2021 (April 30, 2021): 1–8. http://dx.doi.org/10.1155/2021/9963133.

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In the era of Industry 4.0, single-view clustering algorithm is difficult to play a role in the face of complex data, i.e., multiview data. In recent years, an extension of the traditional single-view clustering is multiview clustering technology, which is becoming more and more popular. Although the multiview clustering algorithm has better effectiveness than the single-view clustering algorithm, almost all the current multiview clustering algorithms usually have two weaknesses as follows. (1) The current multiview collaborative clustering strategy lacks theoretical support. (2) The weight of

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