Search Results - (( using function based algorithm ) OR ( basic optimization model algorithm ))

Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems by Din, Fakhrud, Khalid, Shah, Fayaz, Muhammad, Gwak, Jeonghwan, Kamal Z., Zamli, Mashwani, Wali Khan

“…The performance of the fuzzy adaptive teaching learning-based optimization is evaluated against other metaheuristic algorithms including basic teaching learning-based optimization on 23 unconstrained global test functions. …”
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Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach by Wan Solehah, Wan Ahmad

“…The result indicates the performance of the optimized model outperforms the baseline model.…”
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Intelligently tuned weights based robust H∞ controller design for pneumatic servo actuator system with parametric uncertainty by Ali, Hazem Ibrahim, Mohd Noor, Samsul Bahari, Bashi, Sinan Mahmod, Marhaban, Mohammad Hamiruce

“…This paper presents a new method for tuning the weighing functions to design an H∞ controller. Based on a particle swarm optimization (PSO) algorithm the, weighting functions are tuned. …”
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Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller by Zaridah, Mat Zain

“…The contribution of this work is to optimize the base of Fuzzy membership function of the APFLC by using GA technique. …”
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Automated bilateral negotiation with incomplete information in the e-marketplace. by Jazayeriy, Hamid

“…The MGT algorithm is useful to explore the properties of the Pareto-optimal offers. …”
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Heuristic resource allocation algorithm for controller placement in multi-control 5G based on SDN/NFV architecture by Ibrahim, Abeer Abdalla Zakaria, Hashim, Fazirulhisyam, Noordin, Nor Kamariah, Sali, Aduwati, Navaie, Keivan, Fadul, Saber Mohammed Elnour

“…A Greedy Randomized Search (GRS) algorithm was used to solve the dynamic assignment of nodes to controllers to achieve load balancing. …”
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Neural Network – A Black Box Model by Kuok, Kuok King, Chan, Chiu Po, Md. Rezaur, Rahman, Khairul Anwar, Mohamad Said, Chin Mei, Yun

“…A variety of metaheuristic algorithms have been used to train ANN, including Genetic Algorithms (GA), Particle Swarm Optimization (PSO), Simulated Annealing (SA), Ant Colony Optimization (ACO), Tabu Search (TS), and Harmony Search (HS). …”
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Master-leader-slave cuckoo search with parameter control for ANN optimization and its real-world application to water quality prediction by Jaddi N.S., Abdullah S., Malek M.A.

Optimization of Upstream Offshore Oilfield Production Planning under Uncertainty and Downstream Crude Oil Scheduling at Refinery Front-End by Tan Yin Keong, Tan Yin

“…Having validated the model formulation and solution obtained, we believe that the model can be a useful basic tool to assist upper-level management in deciding on an optimal plan for crude oil production from an offshore operation. …”
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Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling by Anuar, Nurul Izah

“…The experimentations of the proposed algorithm are conducted using existing benchmark instances and a published case study on an energy-efficient job-shop model. …”
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Improving neural networks training using experiment design approach by Chong, Wei Kean

“…There are several methods of selecting training data from input space for neural networks which include D-optimal and Max-min design approaches. Consider a function approximation problem (Neural Network using Radial Basic Function structure) and limit the amount of training data, say (m) from N amount of possible data. …”
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EMG motion pattern classification through design and optimization of neural network by Ahsan, Md. Rezwanul, Ibrahimy, Muhammad Ibn, Khalifa, Othman Omran

“…This paper illustrates the classification of EMG signals through design and optimization of Artificial Neural Network (ANN). Different types of ANN models are basically structured with many interconnected network elements which can develop pattern classification strategies based on a set of input/training data. …”
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Long-term optimal planning for renewable based distributed generators and battery energy storage systems toward enhancement of green energy penetration by ALAhmad A.K., Verayiah R., Shareef H.

“…The backward reduction method (BRM) is then applied to streamline the number of generated scenarios, reducing computational efforts. To solve the optimization planning model, a hybrid optimization algorithm is proposed, combining the non-dominating sorting genetic algorithm (NSGAII) and multi-objective particle swarm optimization (MOPSO). …”

Model Identification Using Neuro-Fuzzy Approach by Lemma, T.A.

“…Last section of the chapter deals with three different model training algorithms Least squares based, back-propagation and particle swarm optimization. …”
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Model Identification Using Neuro-Fuzzy Approach by Lemma, T.A.

“…Last section of the chapter deals with three different model training algorithms Least squares based, back-propagation and particle swarm optimization. …”
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EMG motion pattern classification through design and optimization of Neural Network by Md. Rezwanul, Ahsan, Muhammad Ibn, Ibrahimy, Othman Omran, Khalifa

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Power System State Estimation In Large-Scale Networks by NURSYARIZAL MOHD NOR, NURSYARIZAL

“…The gain and the Jacobian matrices associated with the basic algorithm require large storage and have to be evaluated at every iteration, resulting in more computation time. …”
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Catalytic conversion of methane and carbon dioxide in conventional fixed bed and dielectric barrier discharge plasma reactors by Istadi, Istadi

“…Moreover, the operating parameters, such as the CO2/CH4 feed ratio and reactor temperature, and the catalyst compositions, such as wt% CaO and wt% MnO, were optimized by using Weighted Sum of Squared Objective Functions algorithm. …”
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Optimal planning and design of hybrid renewable energy system for rural healthcare facilities / Olatomiwa Lanre Joseph by Olatomiwa Lanre , Joseph

“…Then, utilization of cost-effective optimization algorithm for optimal sizing of the energy resources and other system components with accurate mathematical models for energy management of the entire hybrid system. …”
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Voting algorithms for large scale fault-tolerant systems by Karimi, Abbas

“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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