Search Results - ((((iteration algorithms) OR (generation algorithm))) OR (selection algorithm))

Multiple equations model selection algorithm with iterative estimation method by Kamarudin, Nur Azulia, Ismail, Suzilah

“…In particular, an algorithm on model selection for seemingly unrelated regression equations model using iterative feasible generalized least squares estimation method is proposed. …”
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VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern by Angeline Teoh, Szu Fern

“…This method is used to reduce the stochastic of data generation as the second iteration will have influence of the first iteration data. …”
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Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms by Teoh, Chin Chuang

“…In cluster generating process, the developed BBSI algorithm was used to select the best band combination for generating cluster by using Iterative self- Organizing Data Analysis (ISODATA) technique. …”
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Q-learning whale optimization algorithm for test suite generation with constraints support by Hassan, Ali Abdullah, Salwani, Abdullah, Kamal Z., Zamli, Rozilawati, Razali

“…Experimental results for constraints combinatorial test generation demonstrate that the proposed QWOA-EMC outperforms WOA and performs competitively against other metaheuristic algorithms.…”
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A novel clustering based genetic algorithm for route optimization by Aibinu, Abiodun Musa, Salau, Habeeb Bello, Najeeb, Athaur Rahman, Nwohu, Mark Ndubuka, Akachukwu, Chichebe

“…It was also observed that the introduction of clustering based selection algorithm guaranteed the selection of cluster with the optimal solution in every generation. …”
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Selective harmonic elimination in cascaded H-bridge multilevel inverter using hybrid APSO algorithm / Mudasir Ahmed by Mudasir , Ahmed

“…The simulation results show that the proposed algorithm calculates highly precise firing angles in less number of iterations with the very high capability of tackling the local optima then Bee Algorithm (BA), differential evolution (DE), GA and PSO. …”
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Application of genetic algorithm and JFugue in an evolutionary music generator by Tang, Jia Rou

“…This project explores the application of Genetic Algorithms (GA) with JFugue, which is a Java-based music programming library to develop an Evolutionary Music Generator. …”
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An ensemble of neural network and modified grey wolf optimizer for stock prediction by Das, Debashish

“…Additionally, the research restricts the number of variables through feature selection to enhance the performance of the algorithm. …”
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A combined filter line search and trust region method for nonlinear programming by Chin, Choong Ming, Halim, Abdul, Rashid, A. H. A., Nor, K. M.

“…In the event when the step size has reached a minimum threshold such that the trial iterate is rejected by the filter, the algorithm temporarily exits to a trust region based algorithm to generate iterates that approach the feasible region and also acceptable to the filter. …”
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A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat by Sakamat, Norzehan

“…While hybrid K-MeansCGA combination of fix population size=100 and various size of generation performs better than general KMeans algorithm and hybrid K-MeansCGA combination of fix generation size=100 and various size of populations. …”
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Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

“…Since extreme learning machine is a non-iterative estimation procedure, it is faster than gradient-based algorithms which are iterative. …”
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Hybrid evolutionary-dolphin echolocation programming for sizing optimization of stand-alone photovoltaic systems / Zulkifli Othman by Othman, Zulkifli

“…Initially, Iterative-based Sizing Algorithm (ISA) which uses the non-computational intelligence-based approach is presented to serve as the benchmark for computational intelligence (CI)-based sizing algorithm. …”
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On iterative low-complexity algorithm for optimal antenna selection and joint transmit power allocation under impact pilot contamination in downlink 5g massive MIMO systems by Mohammed Ahmed, Adeeb Ali

“…The proposed Low–complexity iterative algorithm for antenna selection and transmission power helped to choose an accurate number of active RF chains to reduce circuit power consumption, and minimize the reuse of pilot sequences to improve channel estimation. …”
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Intelligent sizing and output prediction techniques for grid-connected photovoltaic system / Shahril Irwan Sulaiman by Sulaiman, Shahril Irwan

“…It was found that the maximum solar electricity requirement from CSA with DG1 was actually capped to the maximum solar electricity that can be generated from CSA with DG2. Apart from that, a novel Iterative Sizing Algorithm (ISA) was also developed to present an iterative approach towards sizing process when there were numerous sets of PV module and inverter need to be considered. …”
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A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites by Din, Fakhrud

“…Many test data generation strategies based on meta-heuristic algorithms such as Simulated Annealing (SA), Tabu Search (TS), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Particle Swarm Optimization (PSO), Harmony Search (HS), Cuckoo Search (CS), Bat Algorithm (BA) and Bees Algorithm have been developed in recent years. …”
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Optimizing tree planting areas through integer programming and improved genetic algorithm by Md Badarudin, Ismadi

“…Therefore, a hybrid algorithm through an incorporation of Integer Programming and Improved Genetic Algorithm was proposed for planting lining design. …”
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Space allocation for examination scheduling using Genetic Algorithm / Alya Kauthar Azman by Azman, Alya Kauthar

“…The system generates and evaluates potential schedules using fitness functions, selection, crossover, and mutation operators to iteratively improve scheduling efficiency. …”
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Hybrid Artificial Bees Colony Algorithms For Optimizing Carbon Nanotubes Characteristics by Mohammad Jarrah, Mu'ath Ibrahim

“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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Genetic Algorithms And Particle Swarm Optimization For Interference Minimization In Mobile Network Channel Assignment Problem by Loh, Ser Lee, Keek, Joe Siang, Wong, Yan Chiew, Woo, Xiu Juan, Lee, Wei Wen

“…This paper presents the study and comparison of Genetic Algorithm (GA) and Particle Swam Optimization (PSO) for CAP in minimizing interference. …”
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Frequency regulation for microgrid using genetic algorithm and particle swarm optimization tuned STATCOM by Saxena N.K., Gao W.D., Kumar A., Mekhilef S., Gupta V.

“…Asynchronous generators; Controllers; Distributed power generation; Electric current regulators; Electric power transmission networks; Errors; Flexible AC transmission systems; Frequency response; Genetic algorithms; IEEE Standards; Iterative methods; MATLAB; Power control; Reactive power; Static synchronous compensators; Classical methods; Compensator current; Current controller; Distributed generators; Frequency regulations; Genetic algorithm and particle swarm optimizations; Microgrid; Power load; Squirrel cage induction generators; Static synchronoi compensator; Particle swarm optimization (PSO)…”