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Parameters extraction of double diode photovoltaic module's model based on hybrid evolutionary algorithm by Muhsen D.H., Ghazali A.B., Khatib T., Abed I.A.

Modified firefly algorithm for directional overcurrent relay coordination in power system protection / Muhamad Hatta Hussain by Hussain, Muhamad Hatta

“…The objectives of the studies are to develop a new optimization technique termed as Modified Firefly Algorithm (MFA) for minimizing the relay operating time, to develop a Multi-Objective Modified Firefly Algorithm (MOMFA) for minimizing both the total relay operating time and relay coordination time and to develop an integrated optimal predictor termed as Modified Firefly Algorithm-Artificial Neural Network (MFA-ANN) for accurate prediction of relay operating time. …”
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VLSI floor planning optimization using genetic algorithm and cross entropy method / Angeline Teoh Szu Fern by Angeline Teoh, Szu Fern

“…DM is optimized using genetic algorithm (GA). GA is a widely used optimization algorithm based on the concept of survival of the fittest. …”
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Parameter characterization of PEM fuel cell mathematical models using an orthogonal learning-based GOOSE algorithm by Manoharan P., Ravichandran S., Kavitha S., Tengku Hashim T.J., Alsoud A.R., Sin T.C.

“…The fuel�cells�(FCs) involve multiple variable quantities with complex non-linear behaviours, demanding accurate modelling to ensure optimal operation. An accurate model of these FCs is essential to evaluate their performance accurately. …”

Crossover and mutation operators of real coded genetic algorithms for global optimization problems by Lim, Siew Mooi

“…Second of all, this study operates within experimental design with Taguchi method to discover the optimal design factors for the two proposed genetic operators. …”
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Intelligent algorithm based modeling of renewable and green energy resources for microgrid optimization by Khamis, Alias

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LASSO-type estimations for threshold autoregressive and heteroscedastic time series models. by Muhammad Jaffri Mohd Nasir

“…A new algorithm of coordinate gradient descent (CGD) is developed to optimize the adaptive LASSO. …”
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Streamflow prediction with large climate indices using several hybrid multilayer perceptrons and copula Bayesian model averaging by Panahi F., Ehteram M., Ahmed A.N., Huang Y.F., Mosavi A., El-Shafie A.

An improved design for cellular manufacturing system associating scheduling decisions by Subhaa, R., Jawahar, N., Ponnambalam, S. G.

“…The proposed model belongs to the class of NP-hard problems. A hybrid heuristic (HH) that has “Simulated Annealing Algorithm (SAA) embedded with Genetic Algorithm (GA)” is proposed. …”
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Optimized scheduling for an airconditioning system based on indoor thermal comfort using the multiobjective improved global particle swarm optimization by Haniff, Mohamad Fadzli, Selamat, Hazlina, Khamis, Nuraqilla, Alimin, Ahmad Jais

“…The main contribution of this paper is a new optimized AC scheduling approach that focuses on indoor thermal comfort using a new multi-objective optimization algorithm, called the improved global particle swarm optimization (IGPSO), which able to find better optimal solutions faster than its original version, the global particle swarm optimization (GPSO) algorithm. …”
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Fuzzy clustering method and evaluation based on multi criteria decision making technique by Sameer, Fadhaa Othman

“…This proposed algorithm is developed based on heuristic method named modified binary particle swarm optimization (MBPSO) with kernel fuzzy clustering method as a fitness function. …”
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Neural network-based prediction models for physical properties of oil palm medium density fiberboard / Faridah Sh. Ismail by Sh. Ismail, Faridah

“…Back-propagation algorithm is a training method widely used in a multilayer perceptron Neural Network model. …”
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Hybrid dynamic scheduling model for flexible manufacturing system with machine availability and new job arrivals by Paslar, Shahla

“…The idea of hybridizing the newly developed biogeography based optimization algorithm (BBO) with variable neighborhood structure (VNS) is proposed in order to produce a high performance initial schedule in terms of minimum completion time, tardiness and flow time within reasonable amount of time. …”
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Dynamic transmit antenna shuffling scheme for hybrid multiple-input multiple-output in layered architecture by Chong, Jin Hui

“…The computational complexity (total number of arithmetic operations) of proposed LC-QR algorithm is significantly lower than the conventional QR decomposition, zero-forcing (ZF) and minimum mean square error (MMSE) detection algorithm. …”
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The conceptual framework of knowledge of large scale and incomplete graphs of skyline queries optimization using machine learning by Noor, Ubair, Hassan, Raini, Dwi Handayani, Dini Oktarina

“…The implemented algorithm to perform such operation was far more efficient, faster and accurate as compared to conventional methods. …”
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A headway and order scheme based mixed integer goal programming model for railway rescheduling / Zuraida Alwadood by Alwadood, Zuraida

“…The model is solved by means of preemptive goal programming technique, using MATLAB r2014a, which automatically generates the optimal solution to the problem. …”
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Improving TRIGA PUSPATI Reactor performance with a PI controller and PSO-optimized fractional order lead-lag compensator by Che Soh, Azura, Mohd Noor, Samsul Bahari, Abdul Rahman, Ribhan Zafira, Abdullah, Nor Arymaswati, Abdul Karim, Julia

“…Currently, the RTP uses a Feedback Controller Algorithm (FCA) based on a Proportional-Integral (PI) controller to improve steady-state error during operation. …”
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Optimal Maintenance Scheduling for Multi-Component E-Manufacturing System by Arab, Ali

“…Then, using genetic algorithm-based software which is called SimRunner and has been embedded by ProModel, the scheduling optimization procedure is run to find optimum maintenance schedule. …”
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Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines by Aker, Elhadi Emhemed Alhaaj Ammar

“…The BayesNet provides the best integrated MLADR fault classifier model better at a 5 % significance level than other deployed algorithms in the intelligent supervised learning model realization. …”
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Two level aggregation scheme with optimization in subframes headers for IEEE 802.11n wireless networks by Noma, Adamu Muhammad

“…By both analytical and simulation, the eA-MSDU improved channel’s utilization by up to 10% and 20% in terms of throughput increase and overhead reduction respectively. Furthermore, a new two-level aggregation model is developed by integrating the eA-MSDU into A-MPDU and designing suitable operating algorithm. …”
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