Search Results - parallel evolution ((based algorithm) OR (_ algorithm))

PMT : opposition based learning technique for enhancing metaheuristic algorithms performance by Hammoudeh, S. Alamri

“…To evaluate the PMT’s performance and adaptability, the PMT was applied to four contemporary metaheuristic algorithms, Differential Evolution, Particle Swarm Optimization, Simulated Annealing, and Whale Optimization Algorithm, to solve 15 well-known benchmark functions as well as 2 real world problems based on the welded beam design and pressure vessel design. …”
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PMT: opposition-based learning technique for enhancing meta-heuristic performance by Alamri, Hammoudeh S., Kamal Z., Zamli

“…To evaluate the PMT's performance and adaptability, the PMT has been applied to four contemporary meta-heuristic algorithms, differential evolution (DE), particle swarm optimization (PSO), simulated annealing (SA), and whale optimization algorithm (WOA), to solve 15 well-known benchmark functions. …”
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Optimization of extractive Automatic Text Summarization using Decomposition-based Multi-objective Differential Evolution and parallelization by Hazmi Wahab, Muhammad Hafizul

“…In order to address this, a novel solution called Decomposition-based Multi-objective Differential Evolution (MODE/D) is proposed. …”
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OPTIMIZATION OF HYBRID-FUZZY CONTROLLER FOR SERVOMOTOR CONTROL USING A MODIFIED GENETIC ALGORITHM by WAHYUNGGORO, OYAS WAHYUNGGORO

“…Many tuning methods for PID controller have been developed, and one of them is based on natural evolution, the genetic algorithm (GA). …”
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Smile Mask Development of Cryptography Performance of MOLAZ Method (MOLAZ-SM) by Shuwandy, Moceheb Lazam

“…Department of Defense and launched in the eighties to the world. Even so, it parallels the evolution of these methods to penetrate systems. …”
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Recognizing complex human activities using hybrid feature selections based on an accelerometer sensor by Zainudin, Muhammad Noorazlan Shah, Sulaiman, Md Nasir, Mustapha, Norwati, Perumal, Thinagaran, Mohamed, Raihani

“…Wearable sensor technology is evolving in parallel with the demand for human activity monitoring applications. …”
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Artificial neural network learning enhancement using Artificial Fish Swarm Algorithm by Hasan, Shafaatunnur, Tan, Swee Quo, Shamsuddin, Siti Mariyam, Sallehuddin, Roselina

“…Artificial Neural Network (ANN) is a new information processing system with large quantity of highly interconnected neurons or elements processing parallel to solve problems.Recently, evolutionary computation technique, Artificial Fish Swarm Algorithm (AFSA) is chosen to optimize global searching of ANN.In optimization process, each Artificial Fish (AF) represents a neural network with output of fitness value.The AFSA is used in this study to analyze its effectiveness in enhancing Multilayer Perceptron (MLP) learning compared to Particle Swarm Optimization (PSO) and Differential Evolution (DE) for classification problems.The comparative results indeed demonstrate that AFSA show its efficient, effective and stability in MLP learning.…”
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Agro-ento bioinformation: towards the edge of reality by Syed Hassan, Syed Tajuddin

“…Bioinformation, in brief, comprises biology, information algorithms, information technology, and communication protocols. …”
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Application Of Genetic Algorithms For Robust Parameter Optimization by Belavendram, N.

“…In this paper, a genetic algorithm is used to study a seven factor non-linear equation for a Wheatstone bridge as the equation to be optimized. …”
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An Efficient Energy Aware Adaptive System-On-Chip Architecture For Real-Time Video Analytics by Ahmed, Hisham Ahmed Ali

“…A careful analysis of the algorithm and efficient utilization of Zynq resources results in highly parallelized and pipelined architecture outperforms the state-of-the-art. …”
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A complexity-reduced digital predistortion for radio frequency power amplifier by Yousif, Siba Monther

“…The performance of the proposed model is assessed using a commercial class-AB power amplifier driven by a 2-carrier Wideband CDMA(WCDMA) signal of 15 MHz bandwidth and Long-Term Evolution (LTE) signals of 15 MHz and 20 MHz bandwidth. …”
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