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A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising
Published 2015“…As the standard DE algorithm is a fixed length optimizer, it is not suitable for solving signal de-noising problems that call for variability. …”
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2
Cloudlet deployment and task offloading in mobile edge computing using variable-length whale and differential evolution optimization and analytical hierarchical process for decisio...
Published 2023“…Enabling more optimality and adaptability to the dynamic nature of CDTO, we propose a novel Variable-Length multi-objective Whale optimization Integrated with Differential Evolution designated as VL-WIDE for joint cloudlet deployment and tasks offloading. …”
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Thesis -
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Optimized differential evolution algorithm for linear frequency modulation radar signal denoising
Published 2013“…The main contention of this thesis is to investigate the development of new optimization technique based on Differential Evolution algorithm (DE), applied for radar signal denoising application. …”
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4
A multi-objective particle swarm optimization algorithm based on dynamic boundary search for constrained optimization
Published 2018“…M-MOPSO is compared with four other algorithms namely, MOPSO, Multi-Objective Grey Wolf Optimizer (MOGWO), Multi-Objective Evolutionary Algorithm based on Decompositions (MOEA/D) and Multi-Objective Differential Evolution (MODE). …”
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Design of digital circuit structure based on evolutionary algorithm method
Published 2008“…It is largely applied to complex optimization problems. EAs introduce a new idea for automatic design of electronic systems; instead of imagine model, abstractions, and conventional techniques, it uses search algorithm to design a circuit. …”
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Genetic ensemble biased ARTMAP method of ECG-Based emotion classification
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A meta-heuristics based input variable selection technique for hybrid electrical energy demand prediction models
Published 2017“…The results show that the neural network optimized with genetic algorithm and trained with an optimally and intelligently selected input vector containing historical load and meteorological variables produced the best prediction accuracy. …”
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Study of nature inspired computing (NIC) technique for optimal reactive power dispatch problems
Published 2017“…In this research, new nature-inspired meta-heuristic optimization algorithms namely moth-flame optimizer (MFO) and Ant Lion Optimizer (ALO) were implemented to address the optimal reactive power dispatch (ORPD) problems. …”
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Variable Global Optimization min-sum (VGOMS) algorithm of decode-and forward-protocol for the relay node in the cooperative channel
Published 2020“…A low complexity min-sum (MS) based algorithm called the Variable Global Optimization min-sum (VGOMS) algorithm has been developed to minimise the error corrective performance. …”
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10
Model predictive control based on Lyapunov function and near state vector selection of four-leg inverter / Abdul Mannan Dadu
Published 2018“…The proposed control algorithm takes advantage of a predefined Lyapunov control law which minimizes the required calculation time by the Lyapunov model equations just once in each control loop to predict future variables. …”
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Variable Global Optimization min-sum (VGOMS) algorithm of decodeand-forward protocol for the relay node in the cooperative channel
Published 2019“…A low complexity min-sum (MS) based algorithm called the Variable Global Optimization min-sum (VGOMS) algorithm has been developed to minimise the error corrective performance. …”
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Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data
Published 2023“…For this purpose, we implemented four types of variable length meta-heuristic searching algorithms, namely VLBHO-Fitness, VLBHO-Position, variable length particle swarm optimization (VLPSO) and genetic variable length (GAVL), and we compared them in terms of classification metrics. …”
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Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data
Published 2023“…For this purpose, we implemented four types of variable length meta-heuristic searching algorithms, namely VLBHO-Fitness, VLBHO-Position, variable length particle swarm optimization (VLPSO) and genetic variable length (GAVL), and we compared them in terms of classification metrics. …”
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Framework of Meta-Heuristic Variable Length Searching for Feature Selection in High-Dimensional Data
Published 2023“…For this purpose, we implemented four types of variable length meta-heuristic searching algorithms, namely VLBHO-Fitness, VLBHO-Position, variable length particle swarm optimization (VLPSO) and genetic variable length (GAVL), and we compared them in terms of classification metrics. …”
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A firefly algorithm based hybrid method for structural topology optimization
Published 2020“…In this paper, a firefly algorithm based hybrid algorithm through retaining global convergence of firefly algorithm and ability to generate connected topologies of optimality criteria (OC) method is proposed as an alternative method to solve stress-based topology optimization problems. …”
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Optimization of hydropower reservoir operation based on hedging policy using Jaya algorithm
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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Thesis -
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Multi-stage thermal-economical optimization of compact heat exchangers: A new evolutionary-based design approach for real-world problems
Published 2015“…Furthermore, the proposed algorithm has shown a superior performance in finding the near-optimum solution for this task when it is compared to the most popular evolutionary algorithms in engineering applications, i.e. genetic algorithm (GA) and particle swarm optimization (PSO).…”
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Optimization Of Bar Linkage By Using Genetic Algorithms
Published 2005“…This thesis presents the method of using simple Genetic Algorithms (GAs) in optimizing the size of bar linkage with discrete design variables and continues design variables. …”
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