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New random approaches of modified adaptive bats sonar algorithm for reservoir operation optimization problems
Published 2024“…The increasing interest among researchers in the application of metaheuristic algorithms for search optimization has resulted in notable progress, especially in tackling single objective optimization problems. …”
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Advances of metaheuristic algorithms in training neural networks for industrial applications
Published 2023“…Backpropagation; Gradient methods; Neural networks; Artificial neural network models; Complex applications; Exploration and exploitation; Gradient-based learning; Industry applications; Meta heuristic algorithm; Meta-heuristic search algorithms; Near-optimal solutions; Optimization…”
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Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…To achieve an optimum waiting and response time this thesis has proposed a new approach utilizing the aforementioned modelling, optimizing and partitioning algorithms. …”
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DESIGN AND EVALUATION OF RESOURCE ALLOCATION AND JOB SCHEDULING ALGORITHMS ON COMPUTATIONAL GRIDS
Published 2012“…The four prime aspects of this work are: firstly, a model of the grid scheduling problem for dynamic grid computing environment; secondly, development of a new web based simulator (SyedWSim), enabling the grid users to conduct a statistical analysis of grid workload traces and provides a realistic basis for experimentation in resource allocation and job scheduling algorithms on a grid; thirdly, proposal of a new grid resource allocation method of optimal computational cost using synthetic and real workload traces with respect to other allocation methods; and finally, proposal of some new job scheduling algorithms of optimal performance considering parameters like waiting time, turnaround time, response time, bounded slowdown, completion time and stretch time. …”
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Optimisation model for scheduling MapReduce jobs in big data processing / Ibrahim Abaker Targio Hashem
Published 2017“…In this study, we aim to optimize task scheduling and resource utilization using an evolutionary algorithm based on the proposed completion time and monetary cost of cloud service models. …”
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Development of an augmented reality based facility layout planning and optimization / Tan Chee Hau
Published 2020“…This study presents an augmented reality (AR) based facility layout planning (FLP) system with an optimization algorithm to assist facility layout designers in decision making. …”
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CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…The solution set (i.e. optimized weight/bias matrix of ANN) provided by the optimized and improved genetic algorithm and modified BP based model is extracted and used in the design and development of a prototype device of the proposed model. …”
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Hybridization of metaheuristic algorithm in training radial basis function with dynamic decay adjustment for condition monitoring / Chong Hue Yee
Published 2023“…RBFN-DDA performs incremental learning wherein its structure expands by adding new hidden units to include new information. …”
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Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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Monograph -
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Hybrid moth flame optimization mppt algorithm for accurate real-time tracking under partially shaded photovoltaic system
Published 2021“…In addition, with the continuous improvement effort and the possibility of a new-comer algorithm can show superior results on the current problem, a new MFO based MPPT algorithm was proposed. …”
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Modified ACS centroid memory for data clustering
Published 2019“…Ant Colony Optimization (ACO) is a generic algorithm, which has been widely used in different application domains due to its simplicity and adaptiveness to different optimization problems. …”
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Voting algorithms for large scale fault-tolerant systems
Published 2011“…To solve this problem and gain benefits of this algorithm, we employed parallel algorithm technique and by using optimal number of processors, we could propose optimal algorithms known as Parallel Average Voting and Parallel Weighted Average Voting which both have optimal time complexity and less calculation cost. …”
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Optimization of RFID network planning for monitoring railway mechanical defects based on gradient-based Cuckoo search algorithm
Published 2020“…In conclusion, this study presented a novel hybrid evolutionary algorithm based on the combination of AHP with GBCS to specify optimal RFID reader positions and amount based on the working train station domain. …”
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A harmony search algorithm for university course timetabli
Published 2012“…The major thrust of this algorithm lies in its ability to integrate the key components of population-based methods and local search-based methods in a simple optimization model. …”
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Particle swarm optimization for NARX structure selection: application on DC motor model / Mohd Ikhwan Abdullah
Published 2010“…This thesis was presents the nonlinear identification of a DC motor using Binary Particle Swarm Optimization (BPSO) algorithm, as a model structure selection method, replacing the typical Orthogonal Least Squares (OLS) used in system identification. …”
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Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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New approach of cryptography algorithm for e- mail applications
Published 2005“…Because of its short time execution and higher authentication, using this algorithm will ensure the security for internet applications.…”
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LASSO-type estimations for threshold autoregressive and heteroscedastic time series models.
Published 2020“…A new algorithm of coordinate gradient descent (CGD) is developed to optimize the adaptive LASSO. …”
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