Search Results - (( variable implementation case algorithm ) OR ( java adaptation optimization algorithm ))

Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

An experimental study of neighbourhood based metaheuristic algorithms for test case generation satisfying the modified condition / decision coverage criterion by Haque, Ariful

“…Late Acceptance Hill Climbing (LAHC) and the Great Deluge Algorithm (GDA) which are our new implementation, Simulated Annealing (SA) and Hill Climbing (HC) are re-implemented to generate test cases satisfying MC/DC criterion for comparative analysis. …”
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Study of nature inspired computing (NIC) technique for optimal reactive power dispatch problems by Sulaiman, Mohd Herwan

“…ORPD problem is a nonlinear optimization problem that involving both equality constraints and inequality constraints. The proposed algorithms are tested on five different case studies which are IEEE 30-bus system with 13 control variables, IEEE 30-bus system with 19 control variables, IEEE 30-bus system with 25 control variables, IEEE 57-bus system with 25 control variables and IEEE 118-bus system with 77 control variables. …”
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Similarity distance measure and prioritization algorithm for test case prioritization in software product line testing by Abd Halim, Shahliza, Abang Jawawi, Dayang Norhayati, Sahak, Muhammad

“…Identified enhancements have been implemented to both techniques for a better adoption of prioritizing SPL test cases. …”
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Slight-Delay Shaped Variable Bit Rate (SD-SVBR) Technique for Video Transmission by Ahmad Suki, Che Mohamed Arif

“…It is designed based on the Shaped VBR (SVBR) algorithm and was implemented in the Network Simulator 2 (ns-2). …”
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A case study on quality of sleep and health using Bayesian networks by Hong , Choon Ong, Chiew , Seng Lee, Chye , Ching Sia

“…The network scores computation is implemented to estimate the fitting of the resulting network of each structural learning algorithm in order to choose the best-fitted network. …”
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Modelling and analysis of sensor fault tolerant control using behavioral approach to systems theory by Ng, Peng Hong

“…Mathematical models of the plants are first derived through the description of the manifest behavior by elimination of the latent variables via a systematic algorithm. Next, the algorithms for obtaining controllers using pole placement techniques are developed based on specified nominal control laws to retain all the desirable trajectories in the plant behavior while rejecting the undesirable ones. …”
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Optimal placement of unified power flow controller by dynamic implementation of system-variable-based voltage-stability indices to enhance voltage stability by Ahmad, S., Albatsh, F.M., Mekhilef, Saad, Mokhlis, Hazlie

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Dynamic Economic Dispatch For Power System by Hussein, Saif Tahseen

“…The performance of the PSO-based developed algorithm was tested on simple case studies with a small number of generation units and limited constraints, and then on more complex case studies with a large number of variables and complicated constraints. …”
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Adopting A Particle Swarm-Based Test Generator Strategy For Variable-Strength And T-Way Testing by S. Ahmed, Bestoun

“…Recently, researchers have started to explore the use of Artificial Intelligence (AI)-based algorithms as t-way (where t indicates the interaction strength) and variable-strength testing strategies. …”
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Development of committee machine models for multiple response optimization problems by Golestaneh, Seyed Jafar

“…The results represent Global Desirability of proposed algorithm is equal or higher than GD of case studies. …”
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Determination of tree stem volume : A case study of Cinnamomum by Noraini Abdullah

“…Illustrations and algorithms are incorporated into the procedures. Non-normal and nonlinear data variables are addressed, hence data characterization is presented. …”
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Effect of input variables selection on energy demand prediction based on intelligent hybrid neural networks by Islam, B., Baharudin, Z., Nallagownden, P.

“…Multiple cases are developed using different optimally selected input variable vectors to train and test the back propagation neural network (BP-NN) and the hybrid model. …”
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An ensemble of neural network and modified grey wolf optimizer for stock prediction by Das, Debashish

“…The research implements stock prediction analysis as a case study for training the neural network by adopting MGWO algorithm. …”
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Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions by Saraswati, Galuh Wilujeng

“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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A swarm intelligent approach for multi-objective optimization of compact heat exchangers by Yousefi M., Yousefi M., Martins Ferreira R.P., Darus A.N.

Optimizing the operation release policy using charged system search algorithm: A case study of klang gates dam, Malaysia by Latif S.D., Marhain S., Hossain M.S., Ahmed A.N., Sherif M., Sefelnasr A., El?shafie A.

Dynamics and predictive control of gas phase propylene polymerization in fluidized bed reactors by Shamiri, A., Hussain, M.A., Mjalli, F.S., Mostoutfi, N., Hajimolana, S.

“…The open loop analysis revealed the nonlinear behavior of the polypropylene fluidized bed reactor, justifying the use of an advanced control algorithm for efficient control of the process variables. …”
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Dynamics and predictive control of gas phase propylene polymerization in fluidized bed reactors by Shamiri, A., Hussain, Mohd Azlan, Mjalli, F.S., Mostoufi, N., Hajimolana, S.

“…The open loop analysis revealed the nonlinear behavior of the polypropylene fluidized bed reactor, justifying the use of an advanced control algorithm for efficient control of the process variables. …”
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Towards large scale unconstrained optimization by Abu Hassan, Malik

“…Therefore in dealing with large scale unconstrained problems with a large number of variables, modifications must be made to the standard implementation of the many existing algorithms for the small scale case. …”
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