Search Results - (( var optimization _ algorithm ) OR ( java application learning algorithm ))

Optimally sizing of Static Var Compensator using Bees Algorithm for cost minimization / Norain Sahari by Sahari, Norain

“…This thesis presents the application of Bees Algorithm (BA) technique to find the optimal sizing of Static Var Compensator (SVC) to achieve the power system economic generation and dispatch. …”
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Determining optimal location of static VAR compensator by means of genetic algorithm by Karami, Mahdi, Mariun, Norman, Ab Kadir, Mohd Zainal Abidin

“…The purpose of this paper is to study a practical and accurate heuristic method known as genetic algorithm (GA) which is used to find the optimal location of Static Var Compensator (SVC) and its appropriate size and setting. …”
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Optimal sizing of static VAR compensator using bees algorithm for cost minimization by Sahari, Norain, Azman, Zulkifli, Ngadiron, Zuraidah, Sim, Sy Yi, Mohd Noh, Faridah Hanim, Mustafa, Farahiyah, Zambri, Nor Aira, Norjali, Rasida

“…This paper presents the application of Bees Algorithm (BA) technique to find the optimal sizing of Static Var Compensator (SVC) to achieve the power system economic generation and dispatch. …”
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Optimal placement of static VAR compensator using genetic algorithms by Mustafa, Mohd. Wazir, Wong, Yan Chiew

“…The developed algorithms have successfully obtained the best solution for optimal placement of SVC in the IEEE 9 buses system and TNB northern area 275kV 14-bus system…”
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Optimal design of three-phase static var compensation system by George M., Bakar M.B.B.A., Basu K.P.

Subjects: “…Optimal design…”

Plagiarism Detection System for Java Programming Assignments by Using Greedy String-Tilling Algorithm by Norulazmi, Kasim

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Optimization of neural network through genetic algorithm searches for the prediction of international crude oil price based on energy products prices by Chiroma, Haruna, Ya’u Gital, Abdulsalam, Abubakar, Adamu, Usman, Mohammed Joda, Waziri, Usman

“…The comparison of the prediction performance accuracy of the propose GANN with Support Vector Machine (SVM), Vector Autoregression (VAR), and Feed Forward NN (FFNN) suggested that the propose GANN was more accurate than the SVM, VAR, and FFNN in the prediction accuracy and time computational complexity. …”
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A variable-capacity-based fuzzy random facility location problem with VaR objective by Wang, Shuming, Watada, Junzo, Shamsul Bahar, Yaakob, Prof. Madya

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Sensitivity-based fuzzy multi-objective portfolio model with Value-at-Risk by Zhang, H., Watada, J., Wang, B.

“…In addition, compared with the VaR-FMOPSM model, our sensitivity-based improved model with the IPSO algorithm also performs better than Genetic Algorithm and Simulate Anneal Algorithm (SA), it provides the same performance on this point. …”
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Optimal location and sizing of SVC using Particle Swarm Optimization technique by Jumaat, S.A., Musirin, I., Othman, M.M., Mokhlis, Hazlie

“…This paper describes optimal location and sizing of static var compensator (SVC) based on Particle Swarm Optimization for minimization of transmission losses considering cost function. …”
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A genetic approach for gateway placement in wireless mesh networks by Awadallah, Hashim, Hassan Abdalla Hashim, Aisha

“…Keywords: Wireless Mesh Network, Gateway Placement, Genetic Algorithm, optimization…”
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Transmission loss minimization using SVC based on particle swarm optimization by Jumaat, S.A., Musirin, I., Othman, M.M., Mokhlis, Hazlie

“…This paper describes optimal sizing of static var compensator (SVC) based on Particle Swarm Optimization for minimization of transmission losses considering cost function. …”
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Optimal operation and control of hybrid power systems with stochastic renewables and FACTS devices: An intelligent multi-objective optimization approach by Premkumar M., Hashim T.J.T., Ravichandran S., Sin T.C., Chandran R., Alsoud A.R., Jangir P.

Subjects:

Developing an intelligent system to acquire meeting knowledge in problem-based learning environments by Chiang, A., Baba, M.S.

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Optimal Placement Of FACTS Devices In Power System Using Computational Intelligence Based Method by Mohammad Haikal Bin Aziz

Multistage artificial immune system for static var compensator planning by Siti Chadijah Mohd Nasir

An Educational Tool Aimed at Learning Metaheuristics by Kader, Md. Abdul, Jamaluddin, Jamal A., Kamal Z., Zamli

“…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment by Ruzita, Ahmad

“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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Optimal Reactive Power Dispatch for Voltage Stability Improvement Considering Line Contingencies using PSO by Nor Rul Hasma, Abdullah, I., Musirin

“…The proposed algorithm gives an optimal setting of control devices such as switchable VAR compensator and able to minimize total transmission losses, improved voltage stability and increase voltage profile of the system. …”
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Optimization of support vector machine parameters in modeling of Iju deposit mineralization and alteration zones using particle swarm optimization algorithm and grid search method by Abbaszadeh M., Soltani-Mohammadi S., Ahmed A.N.

“…Copper deposits; Deposits; Geology; Learning algorithms; Mineralogy; Static Var compensators; Support vector machines; Three dimensional computer graphics; Alteration zones; Grid search; Grid-search method; Mineralization zone; Model Selection; Particle swarm optimization algorithm; Penalty parameters; Performance; Support vector classifiers; Support vectors machine; Particle swarm optimization (PSO); accuracy assessment; algorithm; classification; computer simulation; copper; geological survey; mineral alteration; mineralization; numerical model; ore deposit; parameterization; performance assessment; porphyry; resource assessment; support vector machine; three-dimensional modeling; Iran…”