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Multiple Objective Optimization of Green Logistics Using Cuckoo Searching Algorithm
Published 2016“…MATLAB software is used to validate and evaluate the proposed model. …”
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An enhanced swap sequence-based particle swarm optimization algorithm to solve TSP
Published 2021“…Since there is no known polynomial-time algorithm for solving large scale TSP, metaheuristic algorithms such as Ant Colony Optimization (ACO), Bee Colony Optimization (BCO), and Particle Swarm Optimization (PSO) have been widely used to solve TSP problems through their high quality solutions. …”
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Fuzzy adaptive teaching learning-based optimization for solving unconstrained numerical optimization problems
Published 2022“…The performance of the fuzzy adaptive teaching learning-based optimization is evaluated against other metaheuristic algorithms including basic teaching learning-based optimization on 23 unconstrained global test functions. …”
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On spectral efficiency maximization in a partial joint processing system using a multi-start particle swarm optimization algorithm
Published 2015“…Therefore stochastic multi-start particle swarm optimization algorithm (MSPSOA) is proposed in this paper to achieve backhaul reduction and address the issue of lack of diversity, which is related to the basic particle swarm optimization algorithm (BPSOA). …”
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Modeling and control of a Pico-satellite attitude using Fuzzy Logic Controller
Published 2010“…It is observed that the APFLC showed convincing performance over the entire simulation of the Pico-satellite. Genetic Algorithm (GA) is a computational model inspired by evaluation. …”
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7
Hybrid artificial bee colony algorithm with branch and bound for two–sided assembly line balancing
Published 2018“…Recently, the artificial bee colony (ABC) algorithm was used in the solution process where it was considered as a very useful, effective and well-known algorithm. …”
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Block based motion vector estimation using fuhs16 uhds16 and uhds8 algorithms for video sequence
Published 2011“…In addition, the mentioned block-matching algorithms are the baseline techniques that have been used to further develop all the enhanced or improved algorithms. …”
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Hybrid-discrete multi-objective particle swarm optimization for multi-objective job-shop scheduling
Published 2022“…The experimentations of the proposed algorithm are conducted using existing benchmark instances and a published case study on an energy-efficient job-shop model. …”
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Improving Attentive Sequence-to-Sequence Generative-Based Chatbot Model Using Deep Neural Network Approach
Published 2022“…The strategies applied showed that the final accuracy obtained through the training after implementing a modification in the algorithm is at 81% accuracy rate compared to the basic model that recorded its final accuracy at 79% accuracy rate. …”
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A basic study on hybrid systems for small race car to improve dynamic performance using lap time simulation
“…The realization of the proposed hybrid system requires independent control algorithms for the two power systems, engine and electric motor, that take into consideration the state of the vehicle and the driver’s input; this system can be assumed to be a servo model system with multiple inputs and outputs and analyzed to obtain the optimal operation algorithm. …”
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Evaluation method of rationality of urban landscape facility design based on neural network
Published 2025“…Therefore, this study formulates a scientific and reasonable evaluation index system for the rationality of urban landscape facility design and uses a neural network to carry out intelligent evaluation, in order to obtain optimal evaluation outcomes. …”
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Image Splicing Detection With Constrained Convolutional Neural Network
Published 2019“…Then its hyperparameters will be tuned for optimization. With the trained and tuned CNN model, a cross-database classification evaluation is carried out. …”
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Application of hybrid intelligent systems in predicting the unconfined compressive strength of clay material mixed with recycled additive
Published 2021“…Actually, in these systems, respectively, the weights and biases of the artificial neural network (ANN) were optimized using the particle swarm optimization (PSO) and imperialism competitive algorithm (ICA) to get a higher accuracy compared to a pre-developed ANN model. …”
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Application of hybrid intelligent systems in predicting the unconfined compressive strength of clay material mixed with recycled additive
Published 2021“…Actually, in these systems, respectively, the weights and biases of the artificial neural network (ANN) were optimized using the particle swarm optimization (PSO) and imperialism competitive algorithm (ICA) to get a higher accuracy compared to a pre-developed ANN model. …”
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Power System State Estimation In Large-Scale Networks
Published 2010“…The gain and the Jacobian matrices associated with the basic algorithm require large storage and have to be evaluated at every iteration, resulting in more computation time. …”
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Interval type-2 fuzzy logic control optimize by spiral dynamic algorithm for two-wheeled wheelchair
Published 2020“…The research study embarks on three objectives includes developing Interval Type-2 Fuzzy Logic Control (IT2FLC) as the control system, design a Spiral Dynamic Algorithm (SDA) for IT2FLC in stabilizing the designed double-link twowheeled wheelchair system, and optimize the input-output gains and control parameters. …”
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Form Finding And Shape Change Analysis Of Spine Inspired Bio-Tensegrity Model
Published 2017“…Specifically, this basic study aims to (1) formulate mathematical procedures for finding self-equilibrated configurations of spine biotensegrity structure (SBS) models (2) formulate computational strategy for simulating the shape change of novel SBS models, and (3) evaluate the characteristics of the novel SBS models. …”
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Integrated artificial intelligence-based classification approach for prediction of acute coronary syndrome
Published 2014“…In the development of the “hybrid AI-based” classification models, the proposed model (K1-K2- NN), was basically introduced through combining AI approaches of modified K-NN, genetic algorithm (GA), Fisher’s discriminant ratio (FDR) and class separability criteria (CSC). …”
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Inversion of 2D and 3D DC resistivity imaging data for high contrast geophysical regions using artificial neural networks / Ahmad Neyamadpour
Published 2010“…In order to study the effect of data pool formation in training the neural network, two methods have been used to generate the synthetic data. These methods are M1 and M2, and they basically differ in the type of input-output data used to train the artificial neural network. …”
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