Search Results - (( solution constructing based algorithm ) OR ( using optimization model algorithm ))
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1
Integrated optimal control and parameter estimation algorithms for discrete-time nonlinear stochastic dynamical systems
Published 2011“…The main idea is the integration of optimal control and parameter estimation. In this work, a simplified model-based optimal control model with adjustable parameters is constructed. …”
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Thesis -
2
GENETIC ALGORITHM WITH DEEP NEURAL NETWORK SURROGATE FOR THE OPTIMIZATION OF ELECTROMAGNETIC STRUCTURE
Published 2020“…This paper will report on an initial study of the usage of Genetic Algorithm (GA) merged with Deep Neural Network based surrogate model to optimize simulation for electromagnetic structure. …”
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Final Year Project -
3
Nonlinear auto-regressive model structure selection using binary particle swarm optimization algorithm / Ahmad Ihsan Mohd Yassin
Published 2014“…The algorithm searches the solution space by selecting various model structures and evaluating its fitness. …”
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4
Hybrid ant colony optimization algorithm for container loading problem
Published 2012“…The HACO is applied with its probabilistic decision rule and pheromone feedback, together with the TB heuristic to construct towers of boxes to be arranged into the container in order to find the optimal solution. …”
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5
Ant colony optimization algorithm for load balancing in grid computing
Published 2012“…The proposed algorithm is known as the enhance ant colony optimization (EACO). …”
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Monograph -
6
Topology-aware hypergraph based approach to optimize scheduling of parallel applications onto distributed parallel architectures
Published 2020“…Meta-heuristic algorithms have widely used in HPAs due to their global optimization ability. …”
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7
Ideal combination feature selection model for classification problem based on bio-inspired approach
Published 2020“…Such a finding indicates that the exploitation of bio-inspired algorithms with ideal combination of wrapper/filtered method can contribute in finding the optimal features to be used in data mining model construction.…”
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Book Section -
8
Enhancement of Ant Colony Optimization for Grid Job Scheduling and Load Balancing
Published 2011“…A simulation environment was developed using Java programming to test the performance of the proposed EACO algorithm against existing grid resource management algorithms such as Antz algorithm, Particle Swarm Optimization algorithm, Space Shared algorithm and Time Shared algorithm, in terms of processing time and resource utilization. …”
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9
Enhancing the Sorting Layers in the Initial Stage of High School Timetabling
Published 2020“…The high school timetabling problem (HSTP) is considered as an NP-Complete problem as the optimal solution for it, is still not discovered by any algorithm. …”
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Conference or Workshop Item -
10
An ensemble of neural network and modified grey wolf optimizer for stock prediction
Published 2019“…Widespread models like Particle Swarm Optimization (PSO), Genetic Algorithm (GA), Ant Colony Optimization (ACO), Evolutionary Strategy (ES) and Population-Based Incremental Learning (PBIL) dealing with the specified problems are also explored and compared. …”
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Optimal network reconfiguration and intelligent service restoration prediction technique based on Cuckoo search spring algorithm / Mohamad Izwan Zainal
Published 2022“…In this research, Cuckoo Search Spring Algorithm (CSSA) is proposed to enhance the robustness of algorithm by constructing the optimal network reconfiguration consist of reducing power losses and improve voltage profile with the various loadability factor as the constraint according to load profile, based on single and multiobjective model. …”
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13
Gravitational Search Algorithm based Long Short-term Memory Deep Neural Network for Battery Capacity and Remaining Useful Life Prediction with Uncertainty
Published 2024“…The RUL prediction uncertainty with a 95% confidence interval (CI) is also analyzed. The GSA algorithm optimizes the hyperparameters of the LSTM network to construct an optimal model. …”
Conference Paper -
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Feedforward neural network for solving particular fractional differential equations
Published 2024“…Then, a single hidden layer of FNN based on Chelyshkov polynomials with an extreme learning machine algorithm (SHLFNNCP-ELM) is constructed for solving FDEsC. …”
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Thesis -
15
A multi-depot vehicle routing problem with stochastic road capacity and reduced two-stage stochastic integer linear programming models for rollout algorithm
Published 2021“…As a result, it is shown that a base policy consisting of an exact optimal decision at each decision epoch can be obtained constructively through these reduced two-stage stochastic integer linear programming models. …”
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Article -
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Staff scheduling for a courier distribution centre using evolutionary algorithm
Published 2022“…This paper proposed evolutionary algorithm, namely genetic algorithm as the solution to courier center staff scheduling. …”
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Article -
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Agreement options for negotiation on material location decision of housing development
Published 2020“…It will need the development of trade-off algorithms to analyze value of technical solution in real time. …”
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Article -
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Bee colony optimisation of the travelling salesman problem in light rail systems
Published 2019“…The model was able to generate the optimal route in all cases without any error or miscalculation and could thus be used in any rail transit network in the world to determine the optimal route for multiple stations. © 2018 ICE Publishing: All rights reserved.…”
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Article -
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Crossover and mutation operators of real coded genetic algorithms for global optimization problems
Published 2016“…The rationale behind developing algorithms using real encoding of chromosome representations is the limitations of binary encoding. …”
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Thesis -
20
Development of an integrated scheduling model for handling equipment in automated port container terminals
Published 2014“…In addition, results proved that the modified meta-heuristic algorithm is able to find near optimal solutions and on average, the solutions found by the GA algorithm are only 0.2% worse than the optimal solutions and in the worst case in the test cases this difference is 2.3% which is acceptable. …”
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