Search Results - (( solution simulation model algorithm ) OR ( program implementation learning algorithm ))
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1
A multi-depot vehicle routing problem with stochastic road capacity and reduced two-stage stochastic integer linear programming models for rollout algorithm
Published 2021“…A matheuristic approach based on a reduced two-stage Stochastic Integer Linear Programming (SILP) model is presented. The proposed approach is suitable for obtaining a policy constructed dynamically on the go during the rollout algorithm. …”
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2
FPGA Implementation of Emergency Door Car Entry System
Published 2008“…VHSIC is an acronym for Very High-Speed Integrated Circuits. VHDL can be used to model a digital system at many levels of abstraction ranging from the algorithmic level to the gate level. …”
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Learning Object -
3
Development of self-learning algorithm for autonomous system utilizing reinforcement learning and unsupervised weightless neural network / Yusman Yusof
Published 2019“…In the algorithm development a step-by-step example of the algorithm implementation is presented and then successfully implemented in Lego Mindstorm obstacle avoiding mobile robot as a proof of concept implementation of the hybrid AI algorithm. …”
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Thesis -
4
Virtual reality in algorithm programming course: practicality and implications for college students
Published 2024“…The analysis of learning problems shows the unavailability of interactive learning media that can support various learning styles of students in programming algorithm materials. …”
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5
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 -
6
Simulated annealing algorithm for scheduling divisible load in large scale data grids.
Published 2009“…SA algorithm is integrated with DLT model and compared with the previous approaches. …”
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7
Using simulated annealing algorithm for optimization of quay cranes and automated guided vehicles scheduling
Published 2011“…Comparison of the respective results of the mathematical model and the SA algorithm evidently shows acceptable performance of the proposed SA algorithm in finding good solutions for practical scheduling problems. …”
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8
Simulated annealing algorithm for scheduling divisible load in large scale data grids
Published 2008“…SA algorithm is integrated with DLT model and compared with the previous approaches. …”
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Conference or Workshop Item -
9
Design optimization of valve timing at various engine speeds using Multi-Objective Genetic Algorithm (MOGA)
Published 2008“…This paper involves engine modeling in 1D software simulation environment, GT-Power. …”
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Proceeding Paper -
10
Process Planning Optimization In Reconfigurable Manufacturing Systems
Published 2008“…The five (5) AADTs include; a variant of the simulated annealing algorithm that implements heuristic knowledge at critical decision points, two (2) cooperative search schemes based on a “loose hybridization” of the Boltzmann Machine algorithm with (i) simulated annealing, and (ii) genetic algorithm search techniques, and two (2) modified genetic algorithms. …”
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Thesis -
11
Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation
Published 2023Conference paper -
12
Simulated Kalman Filter algorithms for solving optimization problems
Published 2019“…The proposed population-based SKF algorithm and the single solution-based SKF algorithm use the scalar model of discrete Kalman filter algorithm as the search strategy to overcome these flaws. …”
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13
Simulation Model and Genetic Algorithm to Assembly Line Balancing
Published 2013“…It can combine with Genetic Algorithm system (GAs) to obtain the optimum solution in any type of issue area. …”
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14
Application of intelligence based genetic algorithm for job sequencing problem on parallel mixed-model assembly line
Published 2010“…As the total objective values in most of problems could not be improved by simulated algorithm, it proved the well performing of proposed intelligence based genetic algorithm in reaching the near optimal solutions.…”
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15
A new domain specific scripting language for automated machine learning pipeline
Published 2019“…However, in respond to the implementation difficulty, there exists a limited software tool that support easy implementation for automated machine learning based on Genetic Programming. …”
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16
Rapid software framework for the implementation of machine learning classification models
Published 2021“…However, to implement a complete machine learning model involves some technical hurdles such as the steep learning curve, the abundance of the programming skills, the complexities of hyper-parameters, and the lack of user friendly platform to be used for the implementation. …”
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17
Artificial neural network and inverse solution method for assisted history matching of a reservoir model
Published 2017“…This allows to directly simulate the trained neural network and avoid the use of objective function and optimization algorithm. …”
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18
Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms
Published 2008“…Also, this research involves in developing a machine-learning system and program via genetic algorithm that is capable of performing independent learning capability and optimization for scanning sequence using novel GA operators. …”
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Thesis -
19
Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources
Published 2021“…The proposed DNN algorithm is structured to incorporate initial/boundary conditions in cylindrical coordinates and approximate the solution without the aid of any simulated or training data. …”
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20
Simulating Electrohydrodynamic Ion-Drag Pumping on Distributed Parallel Computing Systems
Published 2017“…Findings: This results show that the parallel algorithm for EHD simulations may provide 4.14 times more speedup over sequential algorithm for large grid sizes. …”
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