Search Results - (( frames machine learning algorithm ) OR ( evolution optimization modified algorithm ))
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A new modified differential evolution algorithm scheme-based linear frequency modulation radar signal de-noising
Published 2015“…A modified crossover scheme called rand-length crossover was designed to fit the proposed variable-length DE, and the new DE algorithm is referred to as the random variable-length crossover differential evolution (rvlx-DE) algorithm. …”
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Application of swarm intelligence optimization on bio-process problems / Mohamad Zihin Mohd Zain
Published 2018“…This modified algorithm called Modified Multi-Objective Particle Swarm Optimization (M-MOPSO) employs a fixed-sized external archive along with a dynamic boundary-based search mechanism to evolve the population. …”
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A refined differential evolution algorithm for improving the performance of optimization process
Published 2011“…Various Artificial Intelligent (AI) algorithms can be applied in solving optimization problems. …”
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Improved chemotaxis differential evolution optimization algorithm
Published 2015“…The social foraging behavior of Escherichia coli has recently received great attention and it has been employed to solve complex search optimization problems.This paper presents a modified bacterial foraging optimization BFO algorithm, ICDEOA (Improved Chemotaxis Differential Evolution Optimization Algorithm), to cope with premature convergence of reproduction operator.In ICDEOA, reproduction operator of BFOA is replaced with probabilistic reposition operator to enhance the intensification and the diversification of the search space.ICDEOA was compared with state-of-the-art DE and non-DE variants on 7 numerical functions of the 2014 Congress on Evolutionary Computation (CEC 2014). …”
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Broadening selection competitive constraint handling algorithm for faster convergence
Published 2020“…In this study, the BSCCH algorithm has been coupled with Differential Evolution algorithm as a proof of concept because it is found to be an efficient algorithm in the literature for constrained optimization problems. …”
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Multiple Objective Optimization of Green Logistics Using Cuckoo Searching Algorithm
Published 2016“…In this paper, a modified Cuckoo searching algorithm is proposed to solve the multiple objective Green Logistics optimization problem. …”
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Fast shot boundary detection based on separable moments and support vector machine
Published 2021“…As a result, the computational cost is reduced in the subsequent stages. Finally, machine learning statistics based on the support vector machine is implemented to detect the cut transitions. …”
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Self-configured link adaptation using channel quality indicator-modulation and coding scheme mapping with partial feedback for green long-term evolution cellular systems
Published 2015“…To achieve this objective, an iterative approach based on swarm intelligence is used to find the optimal CQI threshold at which the competing criteria are optimized. …”
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A centralized localization algorithm for prolonging the lifetime of wireless sensor networks using particle swarm optimization in the existence of obstacles
Published 2017“…So, the travelling distance, power consumption and lifetime of the network will be calculated in both cases for original algorithm and modified algorithm, which is a modified deployment algorithm, and compared between them. …”
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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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A deep reinforcement learning hybrid algorithm for the computational discovery and characterization of small proteins utilizing mycobacterium tuberculosis as a model
Published 2025“…This study presents the development and evaluation of a novel hybrid machine learning algorithm that integrates the strengths of Random Forest and Gradient Boosting models to enhance the prediction of smORFs. …”
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Machine Learning-Enabled Communication Approach for the Internet of Medical Things
Published 2023“…In this paper, a machine learning-enabled shortest path identification scheme is presented to ensure reliable transmission of frames, especially with the minimum possible communication overheads in the IoMT network. …”
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Autotuning PID Controllers for Quadplane Hybrid UAV using Differential Evolution Algorithm
Published 2024“…By iteratively modifying the control settings to achieve optimal performance, the DE algorithm replaces the requirement for manual PID tuning, which can be time-consuming and suboptimal. …”
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Autotuning PID Controllers for Quadplane Hybrid UAV using Differential Evolution Algorithm
Published 2024“…By iteratively modifying the control settings to achieve optimal performance, the DE algorithm replaces the requirement for manual PID tuning, which can be time-consuming and suboptimal. …”
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Designing machine learning frameworks for intelligence and gamification research / Nordin Abu Bakar
Published 2016“…Machine learning frameworks have been utilised to facilitate intelligence as operational mechanism in intelligence embedded system such as learning system, prediction protocol and robot navigation system. …”
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Using predictive analytics to solve a newsvendor problem / S. Sarifah Radiah Shariff and Hady Hud
Published 2023“…Secondly, in solving every Machine Learning problem, there is no one algorithm superior to other algorithms. …”
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An intelligent risk management framework for monitoring vehicular engine health
Published 2022“…We used machine learning and deep learning algorithms to assess the effectiveness of the risk management system’s decision model. …”
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A new modified conjugate gradient coefficient for solving system of linear equations
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Adaptive model predictive control based on wavelet network and online sequential extreme learning machine for nonlinear systems
Published 2015“…Recently, an online sequential extreme learning machine (OSELM) algorithm has been introduced based on extreme learning machine (ELM) theories for single hidden layer feedforward neural networks (SLFN) and has been applied for different online applications. …”
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