Search Results - adaptive operational performance evolution algorithm

Adaptive differential evolution algorithm with fitness based selection of parameters and mutation strategies / Rawaa Dawoud Hassan Al-Dabbagh by Rawaa Dawoud Hassan, Al-Dabbagh

“…Moreover, this work is extended to integrate the SPX crossover operator with the adaptive ARDE algorithm in a new way of implementation in order to make the adaptive ARDE algorithm satisfy both the global and local search requirements. …”
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Performance analyses of adaptive handover decision algorithm using spectrum aggregation in long term evolution - advanced network by Usman, I. H., Nordin, N. K., Omizegba, E. E., Sali, A., Rasid, M. F. A., Hashim, F.

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A comparative study for parameter selection in online auctions by Gan, Kim Soon

“…The bidding strategies applying self-adaptation model are expected to perform better than the deterministic dynamic adaptation because of the nature of the algorithm itself. …”
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Extraction of photovoltaic module model's parameters using an improved hybrid differential evolution/electromagnetism-like algorithm by Muhsen D.H., Ghazali A.B., Khatib T., Abed I.A.

An Efficient Energy Aware Adaptive System-On-Chip Architecture For Real-Time Video Analytics by Ahmed, Hisham Ahmed Ali

“…Embedded vision is bounded by stringent requirements, namely real-time performance, limited energy, and Adaptivity to cope with the standards evolution. …”
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Evolution, design, and future trajectories on bipedal wheel-legged robot: A comprehensive review by Zulkifli, Mansor, Irawan, Addie, Mohammad Fadhil, Abas

“…Emphasizing the need for adaptable, terrain-aware control algorithms, the review explores the untapped potential of machine learning and soft robotics in enhancing performance across diverse operational scenarios. …”
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Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem by Anniza, Hamdan, San Nah, Sze, Say Leng, Goh, Kang Leng, Chiew, Wei King, Tiong

“…Hybridization in evolutionary algorithm mechanisms such as initialization methods, local searches, specific design operators, and self-adaptive parameters enhance the algorithm’s performance. …”
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Chaotic self-adaptive interior search algorithm to solve combined economic emission dispatch problems with security constraints by Rajagopalan A., Kasinathan P., Nagarajan K., Ramachandaramurthy V.K., Sengoden V., Alavandar S.

Reservoir system modelling using nondominated sorting genetic algorithm in the framework of climate change by Nurul Nadrah Aqilah, Tukimat

“…The statistics of climate change variation and the growth of evolution method inspire the development of a sustainable and long term reservoir operation system. …”
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Crossover and mutation operators of real coded genetic algorithms for global optimization problems by Lim, Siew Mooi

“…Throughout the years, there has been a shift in focus on constructing new crossover and mutation operators to improve the performance of GA in function optimization. …”
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Mobility management for seamless handover in carrier aggregation heterogeneous networks deployment scenario of long term evolution-advanced by Ahmed-Abdulazeez, Mariam Ovayioza

“…The HHPO and the MC-HOD algorithms achieves significant enhancement compared to the conventional and other algorithms examined. …”
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A guided hybrid k-means and genetic algorithm models for children handwriting legibility performance assessment / Norzehan Sakamat by Sakamat, Norzehan

“…K-Means algorithm a popular efficient clustering techniques and genetic algorithm a widely used evolutionary algorithm and known for its adaptive nature were combined to determine the level of handwriting legibility for each child. …”
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Evolving fuzzy grammar for crime texts categorization by Mohd Sharef, Nurfadhlina, Martin, Trevor

“…Results show that the EFG algorithm produces results that are close in performance with the other ML methods while being highly interpretable, easily integrated into a more comprehensive grammar system and with lower model retraining adaptability time.…”
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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

“…These systems have received greater attention in recent years, where many studies have performed to find the optimal design without analyzing the operational performance. …”
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Impacting clinical evaluation of anterior talofibular ligament injuries through analysis of ultrasound images by Singh, V., Elamvazuthi, I., Jeoti, V., George, J., Swain, A., Kumar, D.

“…The enhanced contrast image is further optimized by the particle swarm optimization algorithm. Thereafter, the optimized image is processed by the Chan-Vese method to extract the ATFL region through curve evolution; then the resultant image smoothed by morphological operation. …”
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Impacting clinical evaluation of anterior talofibular ligament injuries through analysis of ultrasound images by Singh, V., Elamvazuthi, I., Jeoti, V., George, J., Swain, A., Kumar, D.

“…The enhanced contrast image is further optimized by the particle swarm optimization algorithm. Thereafter, the optimized image is processed by the Chan-Vese method to extract the ATFL region through curve evolution; then the resultant image smoothed by morphological operation. …”
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Techno-economic evaluation of off-grid hybrid renewable energy system for rural resort electrification in Malaysia / Monowar Hossain by Monowar, Hossain

“…For these purposes, the standalone ANFIS, ANFIS-PSO (particle swarm optimization),ANFIS-GA (genetic algorithm) and ANFIS-DE (differential evolution) prediction algorithms have been developed in MATLAB platform. …”
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The superiority of feasible solutions-moth flame optimizer using valve point loading by Alam, Mohammad Khurshed, Sulaiman, Mohd Herwan, Ferdowsi, Asma, Sayem, MD Shaoran, Ringku, Md Mahfuzer Akter, Foysal, Md.

“…The MFO, Grey Wolf Optimizer (GWO), Success-history-based Parameter Adaptation Technique of Differential Evolution - Superiority of Feasible Solutions (SHADE-SF), and Superiority of Feasible Solutions-Moth Flame Optimizer (SF-MFO) algorithms are applied to address the OPF problem with two objective functions: (1) reducing energy production costs and (2) minimizing power losses. …”
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