Search Results - (( using optimization modified algorithm ) OR ( using evolution search algorithm ))
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1
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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2
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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3
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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4
Hybrid genetic algorithm with multi-parents recombination for job shop scheduling problems / Ong Chung Sin
Published 2013“…Modification on the path by using neighborhood search significantly reduces the total length of the makespan. …”
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5
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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6
Development of an islanding detection scheme based on combination of slantlet transform and ridgelet probabilistic neural network in distributed generation
Published 2019“…Furthermore, to evaluate the efficiency of the proposed modified differential evolution for the training of ridgelet probabilistic neural network, four statistical search techniques, namely, particle swarm optimization, genetic algorithm, simulated angling, and classical differential evolution are used and their results are compared. …”
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7
An improved negative selection algorithm based on the hybridization of cuckoo search and differential evolution for anomaly detection
Published 2018“…CSDE capabilities of global search, and use of L´evy flight facilitates the effectiveness of the detector set in the search space. …”
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8
Crossover-first differential evolution for improved global optimization in non-uniform search landscapes
Published 2015“…The differential evolution (DE) algorithm is currently one of the most widely used evolutionary-based optimizers for global optimization due to its simplicity, robustness and efficiency. …”
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9
Hybrid algorithm for NARX network parameters' determination using differential evolution and genetic algorithm
Published 2013“…A hybrid optimization algorithm using Differential Evolution (DE) and Genetic Algorithm (GA) is proposed in this study to address the problem of network parameters determination associated with the Nonlinear Autoregressive with eXogenous inputs Network (NARX-network). …”
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10
Comparison between Lamarckian Evolution and Baldwin Evolution of neural network
Published 2006“…There are two basic strategies in using hybrid GAs, Lamarckian and Baldwinian evolution. …”
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11
VISUALIZATION OF GENETIC ALGORITHM BASED ON 2-D GRAPH TO ACCELERATE THE SEARCHING WITH HUMAN INTERVENTIONS.
Published 2012“…Visualization techniques help in understanding the searching behaviour of Genetic Algorithm. lt also makes possible the user interactions during the searching process. …”
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12
Optimization of modified Bouc–Wen model for magnetorheological damper using modified cuckoo search algorithm
Published 2021“…A comparison was done against particle swarm optimization, genetic algorithm, and sine–cosine algorithm, where the modified cuckoo search algorithm showed the lowest root mean square error and fastest convergence rate among the three algorithms.…”
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13
Two level Differential Evolution algorithms for ARMA parameters estimatio
Published 2013“…The performance of the algorithm is evaluated using both simulated ARMA models and practical rotary motion system. …”
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Proceeding Paper -
14
Improved Differential Evolution-Based MPPT Algorithm Using SEPIC for PV Systems Under Partial Shading Conditions and Load Variation
Published 2018“…Thus, an improved global search space differential evolution algorithm for tracking the GMPP is introduced in this paper. …”
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15
Reliability assessment of power generation systems using intelligent search based on disparity theory
Published 2017“…Disparity evolution is used to enhance the performance of the probability of mutation in a genetic algorithm (GA) by incorporating features from the paradigm into the disparity theory. …”
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16
A novel quasi-oppositional modified Jaya algorithm for multi-objective optimal power flow solution
Published 2018“…The proposed algorithm is scrutinized and validated using the modified IEEE 30-bus test system. …”
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17
Multiobjective optimization of bioethanol production via hydrolysis using hopfield- enhanced differential evolution
Published 2014“…In this chapter, the weighted sum scalarization approach is used in conjunction with three meta-heuristic algorithms: Differential Evolution (DE), Hopfield-Enhanced Differential Evolution (HEDE), and Gravitational Search Algorithm (GSA). …”
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18
Reliability Assessment of Power Generation Systems Using Intelligent Search Based on Disparity Theory
Published 2017“…Disparity evolution is used to enhance the performance of the probability of mutation in a genetic algorithm (GA) by incorporating features from the paradigm into the disparity theory. …”
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19
Wind farm layout design using modified particle swarm optimization algorithm
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20
Two-stage feature selection using ranking self-adaptive differential evolution algorithm for recognition of acceleration activity
Published 2018“…Consequently, this paper proposes a ranking self-adaptive differential evolution (rsaDE) feature selection algorithm. The proposed algorithm is capable of selecting the optimal feature subsets while improving the recognition of acceleration activity using a minimum number of features. …”
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