Search Results - (( adaptive _ different evolution algorithm ) OR ( adaptive two different evolutionary algorithm ))

Algorithmic design issues in adaptive differential evolution schemes: Review and taxonomy by Al-Dabbagh, Rawaa Dawoud, Neri, Ferrante, Idris, Norisma, Baba, Mohd Sapiyan

“…DE is very sensitive to its parameter settings and mutation strategy; thus, this study aims to investigate these settings with the diverse versions of adaptive DE algorithms. This study has two main objectives: (1) to present an extension for the original taxonomy of evolutionary algorithms (EAs) parameter settings that has been overlooked by prior research and therefore minimize any confusion that might arise from the former taxonomy and (2) to investigate the various algorithmic design schemes that have been used in the different variants of adaptive DE and convey them in a new classification style. …”
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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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A comparative study of evolutionary algorithms and adapting control parameters for estimating the parameters of a single-diode photovoltaic module's model by Muhsen D.H., Ghazali A.B., Khatib T., Abed I.A.

Recent Evolutionary Algorithm Variants for Combinatorial Optimization Problem by Anniza, Hamdan, San Nah, Sze, Say Leng, Goh, Kang Leng, Chiew, Wei King, Tiong

“…The adaptability of evolutionary algorithm mechanisms provides diverse approaches to handle combinatorial optimization challenges. …”
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Parameter extraction of photovoltaic module using hybrid evolutionary algorithm by Muhsen D.H., Ghazali A.B., Khatib T.

Developing a hybrid model for accurate short-term water demand prediction under extreme weather conditions: a case study in Melbourne, Australia by Zubaidi S.L., Kumar P., Al-Bugharbee H., Ahmed A.N., Ridha H.M., Mo K.H., El-Shafie A.

“…Hybrid model development included the optimization of ANN coefficients (its weights and biases) using adaptive guided differential evolution algorithm. Post-optimization ANN model was trained using eleven different leaning algorithms. …”

Broadening selection competitive constraint handling algorithm for faster convergence by Shaikh, T.A., Hussain, S.S., Tanweer, M.R., Hashmani, M.A.

“…The median convergence traces have been compared with two different algorithms based on differential evolution, i:e: Ensemble of Constraint Handling Techniques (ECHT) and Stochastic Ranking Differential Evolution (SRDE). …”
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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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Adaptive route optimization for mobile robot navigation using evolutionary algorithm by Kit Guan Lim, Guan Lim, Yoong Hean Lee, Hean Lee, Min Keng Tan, Keng Tan, Hou, Pin Yoong, Tienlei, Wang, Tze, Kenneth Kin Teo

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Parallel distributed genetic algorithm development based on microcontrollers framework by Krishnan P.S., Kiong T.S., Koh J.

Adaptive Embedded Clonal Evolutionary Programming (AECEP) for optimal Distributed Generation (DG) location and sizing in a distribution system by Nur Zahirah, Mohd Ali

“…The purpose of this thesis is to presents a new technique namely Adaptive Embedded Clonal Evolutionary Programming (AECEP). …”
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Adaptable algorithms for performance optimization of dynamic batch manufacturing processes by Teo, Kenneth Tze Kin

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Enhancing solid oxide fuel cell efficiency through advanced model identification using differential evolutionary mutation fennec fox algorithm by Singla, Manish Kumar, Gupta, Jyoti, Kumar, Ramesh, Jangir, Pradeep, Louzazni, Mohamed, Giri, Nimay Chandra, Al Gburi, Ahmed Jamal Abdullah, EI‑Kenawy, E. I.‑Sayed M., Alharbi, Amal H.

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

“…In this work, three different models of genetic algorithms are considered. …”
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Channel quality indicator for long term evolution system based on adaptive threshold feedback compression scheme by Abdulhasan, Muntadher Qasim

“…This thesis proposes an adaptive feedback algorithm that uses a threshold scheme to enhance the system throughput while maintaining low Block Error Rate (BLER), Bit Error Rate (BER), and overhead. …”
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Evolution strategy for collaborative beamforming in wireless sensor networks by Wong, Chen How

“…It becomes a vital problem to achieve CB as the distributed sensor nodes are unaware of their phase relationship. An iterative algorithm using evolution strategy (ES) is proposed to achieve phase alignment at the intended location in static channels, which require one-bit feedback from the receiver destination. …”
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Adaptive medium access control protocol of Wifi-Halow for home machine-to-machine network by Liew, Jiun Terng

“…Therefore, work can be done on these aspects to improve its performance and introduce a new dimension of adaptation. Firstly, this work proposed a novel algorithm known as probability-based opportunity dynamic adaptation (PODA) of CW for home M2M network. …”
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Adapting perturbation voltage in PV array with power point tracking and differential evolution by Nurul Izyan Kamaruddin, Ahmad Razani Haron, Min Keng Tan, Soo Siang Yang, Hui Hwang Goh, Kenneth Tze Kin Teo

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Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio... by Daba, Layth Muwafaq Abdulhussein

“…Unlike the existing optimization algorithm, VL-WIDE features the capability of searching different lengths of solutions to cover the variable number of cloudlets for deployment. …”
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Hybrid harmony search algorithm for continuous optimization problems by Ala’a Atallah, Hamad Alomoush

“…The IHS-GWO is evaluated using two standard benchmarking sets and two real-world optimization problems. …”
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