Search Results - (( software solution using algorithm ) OR ( evolution optimization _ algorithm ))

Multiple Objective Optimization of Green Logistics Using Cuckoo Searching Algorithm by Wang, Wei, Liu, Yao

“…Basically, Cuckoo searching algorithm imitates the natural evolution of a population with initial solutions. …”
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Harmonic Elimination Pulse Width Modulation Using Differential Evolution Technique For Three Phase Voltage Source Inverter by Kamisman, Norazelina

“…Computation of DE algorithm and simulation of voltage source inverter using the calculated switching angles are carried out by using Matlab/Simulink software package. …”
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Multi-objective optimization of all-wheel drive electric formula vehicle for performance and energy efficiency using evolutionary algorithms by Tey, Jing Yuen, Ramli, Rahizar

“…Results show that the non-dominated sorting genetic algorithm II outperforms the constrained multi-objective evolutionary algorithm based on decomposition by using differential evolution in obtaining a wider distributed Pareto solution and converges at a relatively shorter time frame. …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Tay, Kim Gaik, Huong, Audrey, Sathasivam, Saratha, Majahar Ali, Majid Khan

“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majid Khan bin Majahar Ali, Majid Khan bin Majahar Ali

“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…The SRBFNN’s objective function that corresponds to Satisfiability logic programming can be minimized by different algorithms, including Genetic Algorithm (GA), Evolution Strategy Algorithm (ES), Differential Evolution Algorithm (DE), and Evolutionary Programming Algorithm (EP). …”
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Software testing optimization for large systems using agent-based and NSGA-II algorithms by Jamil, Muhammad Abid, Nour, Mohamed Kidher, Awang Abu Bakar, Normi Sham

“…Consequently, a multi-objective optimization technique can be used to optimize the large system testing process. …”
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Multi-objective Optimization of Biochemical System Production Using an Improve Newton Competitive Differential Evolution Method by Mohd Arfian, Ismail, Mezhuyev, Vitaliy, Safaai, Deris, Mohd Saberi, Mohamad, Shahreen, Kasim, Saedudin, Rd Rohmat

“…Due to that, this study proposed and improved a method that comprises with Newton method, differential evolution algorithm (DE) and competitive co-evolutionary algorithm(ComCA). …”
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Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh by Rawaa Dawoud Hassan, Al-Dabbagh

“…Differential evolution (DE) is a simple yet powerful evolutionary algorithm (EA). …”
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Genetic Mutation of Cowpea as a Constrained Stochastic Optimization Problem in Sustainability by Emmanuel, Okewu, Kehinde, Okewu, Siti Sarah, Maidin, Wong, Ling Shing

“…Our experiments with genetic algorithm as a stochastic optimizer, confirmed that the evolution from the initial random string (initial cowpea species) to the target string (optimal cowpea solution) was smeared by uncertainties in the optimization-for-sustainability effort. …”
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Automated Student Timetable Scheduling System based on Genetic Algorithm by Amirul Azuani, Romlee, Noor Ain, Rosly, Meng, Chuan Haw

“…Genetic algorithm works based on natural evolutions that comprises of several iterations. …”
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Optimizing crystal size distribution based on different cooling strategies in batch crystallization process by Siti Zubaidah, Adnan, Noor Asma Fazli, Abdul Samad

“…The crystallization process was developed and simulated in Matlab software using a potash alum in the water system. Four optimization algorithms were proposed with different objective functions, such as maximizing mean crystal size (I), minimizing coefficient of variation (II), minimizing nucleus-grown crystals (III), and maximizing CSD (IV). …”
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A refined differential evolution algorithm for improving the performance of optimization process by A. R., Yusoff, Nafrizuan, Mat Yahya

“…Various Artificial Intelligent (AI) algorithms can be applied in solving optimization problems. …”
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Two level Differential Evolution algorithms for ARMA parameters estimatio by Salami, Momoh Jimoh Emiyoka, Tijani, Ismaila, Aibinu, Abiodun Musa

“…The problem of determining simultaneously the model order and coefficient of an Autoregressive Moving Average (ARMA) model is examined in this paper. An Evolutionary Algorithm (EA) comprising two-level Differential Evolution (DE) optimization scheme is proposed. …”
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Comparison between Lamarckian Evolution and Baldwin Evolution of neural network by Taha, Imad, Inazy, Qabas

“…We presented hybrid genetic algorithm for optimizing weights as well as the topology of artificial neural networks, by introducing the concepts of Lamarckian and Baldwin evolution effects. …”
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Performance analysis of hybrid renewable energy systems used for rural electrification in Malaysia / Laith Mahmoud Mohammad Halabi by Laith Mahmoud, Mohammad Halabi

“…HOMER software and MATLAB are used in this work. The comparison of the existing systems with the optimized scenarios indicates that the existing systems have not optimally selected prior installation. …”
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Broadening selection competitive constraint handling algorithm for faster convergence by Shaikh, T.A., Hussain, S.S., Tanweer, M.R., Hashmani, M.A.

“…In this study, the BSCCH algorithm has been coupled with Differential Evolution algorithm as a proof of concept because it is found to be an efficient algorithm in the literature for constrained optimization problems. …”
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