Search Results - (( evolution estimation based algorithm ) OR ( evolution optimization bat algorithm ))

Multi-Swarm bat algorithm by Taha A.M., Chen S.-D., Mustapha A.

“…In this study a new Bat Algorithm (BA) based on multi-swarm technique called the Multi-Swarm Bat Algorithm (MSBA) is proposed to address the problem of premature convergence phenomenon. …”

Mixed Unscented Kalman Filter and differential evolution for parameter identification by Legowo, Ari, Mohamad, Zahratu H., Park, HoonCheol

“…Next, its parameters are identified using mixed Unscented Kalman Filter (UKF) and Differential Evolution (DE) based on the experimental data. DE algorithm is integrated into the UKF algorithm to optimize the Kalman gain obtained. …”
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LEMABE: a novel framework to Improve analogy-based software cost estimation using learnable evolution model by Dashti, Maedeh, Gandoman, Taghi Javdani, Adeh, Dariush Hasanpoor, Zulzalil, Hazura, Md Sultan, Abu Bakar

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Quality of service and energy efficient aware (QEEA) scheduling algorithm for long term evolution (LTE) network / Nurulanis Mohd Yusoff by Mohd Yusoff, Nurulanis

“…Basically, the QEEA is based on the Time Domain (TD) and Frequency Domain (FD) scheduling where it is dependent on the QoS requirements to allocate resources. The proposed algorithm is compared against other scheduling algorithms, namely, the Channel and QoS Aware (CQA), Priority Set Scheduler (PSS), Proportional Fair (PF), Maximum Throughput (MT) and Blind Average Throughput (BAT). …”
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Parameter extraction of photovoltaic module using hybrid evolutionary algorithm by Muhsen D.H., Ghazali A.B., Khatib T.

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.

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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Investigation and validation of an eleven level symmetric modular multilevel inverter using grey wolf optimization and differential evolution control algorithm for solar PV applica... by Stonier, A.A., Chinnaraj, G., Kannan, R., Mani, G.

“…Purpose: This paper aims to examine the design and control of a symmetric multilevel inverter (MLI) using grey wolf optimization and differential evolution algorithms. Design/methodology/approach: The optimal modulation index along with the switching angles are calculated for an 11 level inverter. …”
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Parameters extraction of double diode photovoltaic module's model based on hybrid evolutionary algorithm by Muhsen D.H., Ghazali A.B., Khatib T., Abed I.A.

Reliability assessment of power generation systems using intelligent search based on disparity theory by Kadhem, Athraa Ali, Abdul Wahab, Noor Izzri, Aris, Ishak, Jasni, Jasronita, Abdalla, Ahmed N.

“…In this paper, a novel optimization technique named the disparity evolution genetic algorithm (DEGA) is proposed for reliability assessment of power generation. …”
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Using the evolutionary mating algorithm for optimizing deep learning parameters for battery state of charge estimation of electric vehicle by Mohd Herwan, Sulaiman, Zuriani, Mustaffa, Nor Farizan, Zakaria, Mohd Mawardi, Saari

“…According to the simulation results, the proposed EMA-DL algorithm was found to outperform all the other compared algorithms based on the evaluated metrics. …”
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Reliability Assessment of Power Generation Systems Using Intelligent Search Based on Disparity Theory by Kadhem, Athraa Ali, Noor Izzri, Abdul Wahab, Ishak, Aris, Jasronita, Jasni, Abdalla, Ahmed N.

“…In this paper, a novel optimization technique named the disparity evolution genetic algorithm (DEGA) is proposed for reliability assessment of power generation. …”
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Balancing Exploitation And Exploration Search Behavior On Nature-Inspired Clustering Algorithms by Alswaitti, Mohammed Y. T.

“…Hence, this research has proposed three enhanced frameworks, namely, Optimized Gravitational-based (OGC), Density-Based Particle Swarm Optimization (DPSO), and Variance-based Differential Evolution with an Optional Crossover (VDEO) frameworks for data clustering. …”
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Hybrid DE-PEM algorithm for identification of UAV helicopter by Tijani, Ismaila, Akmeliawati, Rini, Legowo, Ari, Budiyono, Agus, Abdul Muthalif, Asan Gani

“…Design/methodology/approach – In this study, flight data were collected and analyzed; MATLAB-based system identification algorithm was developed using DE and PEM; parameterized state-space model parameters were estimated using the developed algorithm and model dynamic analysis. …”
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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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Channel quality indicator for long term evolution system based on adaptive threshold feedback compression scheme by Abdulhasan, Muntadher Qasim

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A Bayesian parameter learning procedure for nonlinear dynamical systems via the ensemble Kalman filter by Ur Rehman, M.J., Dass, S.C., Asirvadam, V.S.

“…Based on observations made from stochastic dynamical systems, we consider the issue of parameter learning, and a related state estimation problem. …”
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Multi-Objective Hybrid Algorithm For The Classification Of Imbalanced Datasets by Saeed, Sana

“…The proposed algorithm is grounded on the two famous metaheuristic algorithms: cuckoo search (CS) and covariance matrix adaptation evolution strategy (CMA-es). …”
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Handover Decision-Making Algorithm for 5G Heterogeneous Networks by Mark Irwin Goh, Abbas Ibrahim Mbulwa, Hoe, Tung Yew, Aroland Kiring, Chung, Seng Kheau, Ali Farzamnia, Ali Chekima, Manas Kumar Haldar

“…The evolution of 5G small cell networks has led to the advancement of vertical handover decision-making algorithms. …”
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Q-learning based vertical handover decision algorithm in LTE-A two-tier macrocell-femtocell systems / Ammar Bathich by Bathich, Ammar

“…To achieve these requirements, small cells have been deployed intensively by Long Term Evolution (LTE) networks operators beside conventional base station structure to provide customers with better service and capacity coverage. …”
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