Search Results - (( features generation using algorithm ) OR ( simulation optimization method algorithm ))
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1
Collaborative simulated annealing genetic algorithm for geometric optimization of thermo-electric coolers
Published 2015“…In this chapter, the technical issues of TECs were discussed. After that, a new method of optimizing the dimension of TECs using collaborative simulated annealing genetic algorithm (CSAGA) to maximize the rate of refrigeration (ROR) was proposed. …”
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Book -
2
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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3
Collaborative simulated annealing genetic algorithm for geometric optimization of thermo-electric coolers
Published 2016“…In this chapter, the technical issues of TECs were discussed. After that, a new method of optimizing the dimension of TECs using collaborative simulated annealing genetic algorithm (CSAGA) to maximize the rate of refrigeration (ROR) was proposed. …”
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4
Hybrid moth flame optimization mppt algorithm for accurate real-time tracking under partially shaded photovoltaic system
Published 2021“…Photovoltaic (PV) module is a packed solar cell, used for generating electricity from the sun’s energy. …”
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5
Sine-cosine optimization-based bijective substitution-boxes construction using enhanced dynamics of chaotic map
Published 2018“…This paper proposes a novel method of constructing strong substitution-boxes (S-boxes) of order n (4 ≤ n ≤ 8) based on a recent optimization algorithm known as sine-cosine algorithm (SCA). …”
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6
Task scheduling in cloud computing environment using hybrid genetic algorithm and artificial bee colony
Published 2022“…During the methodology chapter, a comprehensive investigation has been done to ascertain the proposed method that can be adopted such as algorithms involved, project flow, and simulation. …”
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Academic Exercise -
7
Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun
Published 2021“…In addition, the confidence level was built using the percentile-t-method (or bootstrap-t-method). …”
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8
Modelling of optimized hybrid debris flow using airborne laser scanning data in Malaysia
Published 2019“…The general objective of the study was the development of optimized hybrid debris flow models using airborne laser scanning data and Machine learning algorithms in Malaysia. …”
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9
Deep Reinforcement Learning For Control
Published 2021“…The complete project is carried out in the CARLA simulator to determine how to operate in discrete action space using Deep Reinforcement Learning (DRL) algorithms. …”
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Monograph -
10
Swarm Evolutionary Programming Method for Optimal Under-Frequency Load Shedding Scheme
Published 2017“…This thesis proposed a new method of incorporating swarm features into the optimization algorithm of Classical Evolutionary Programming (CEP) to derive optimal settings for the UFLS scheme. …”
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11
A novel islanding detection technique using modified Slantlet transform in multi-distributed generation
Published 2019“…Islanding and non-islanding events are simulated for a multi-distributed generations system and used to assess the performance of the proposed anti-islanding protection method. …”
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Article -
12
Long-term optimal planning for renewable based distributed generators and plug-in electric vehicles parking lots toward higher penetration of green energy technology
Published 2025“…A hybrid optimization algorithm addresses the proposed objectives, combining the non-dominated sorting genetic algorithm (NSGA-II) and multi-objective particle swarm optimization (MOPSO) to minimize the three distinct objective functions concurrently. …”
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13
Multi-parametric optimization of aerodynamic performance and pedestrian crash in sedan front-end profiles
Published 2025“…A multiobjective optimization framework was developed using computational simulations, mathematical modelling, and evolutionary algorithms. …”
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14
The classification of wink-based eeg signals by means of transfer learning models
Published 2021“…This study aimed to explore the performance of different pre-processing methods, namely Fast Fourier Transform, Short-Time Fourier Transform, Discrete Wavelet Transform, and Continuous Wavelet Transform (CWT) that could allow TL models to extract features from the images generated and classify through selected classical ML algorithms . …”
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15
Enhancing Autonomous Guided Vehicles with Red-Black TOR Iterative Method
Published 2023“…By carefully choosing the optimal parameter values, the suggested B-MTOR improved the computational execution of the algorithm. …”
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16
Development of robust procedures for partial least square regression with application to near infrared spectral data
Published 2021“…In the in-processing, the PLSR model is very sensitive to the optimal number of PLS components used in the model fitting process. …”
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17
Hierarchical extreme learning machine based reinforcement learning for goal localization
Published 2017“…H-ELM algorithm was used in this work to find good features for effective representation. …”
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Proceeding Paper -
18
Optimization of turning parameters using genetic algorithm method
Published 2008“…The simulation based on Genetic Algorithm are successful develop and the optimum parameters values are obtained from the simulation.…”
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Undergraduates Project Papers -
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Hybrid firefly and particle swarm optimization algorithm for multi-objective optimal power flow with distributed generation
Published 2022“…This thesis proposes and simulates the three novel optimization algorithms to handle DG allocation, different single-objective, and multi-objective OPF problems. …”
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20
A discrete simulated kalman filter optimizer for combinatorial optimization problems
Published 2022“…An example of a numerical algorithm is the simulated Kalman filter (SKF). Various method has been introduced as an extension of a numerical algorithm to adapt it to a discrete search space. …”
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