Search Results - (( java implementation path algorithm ) OR ( using complex flow algorithm ))
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1
Heavy Transportation Shortest Route using Dijkstra’s algorithm (HETRO) / Nurul Aqilah Ahmad Nezer
Published 2017“…The development tools used in developing this project is NetBeans by using Java for the implementation of the coding. The methodology that used for developing this system is the Dijkstra’s algorithm. …”
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2
Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…BST inserts the nodes in the way that the Dijkstra’s can find the empty parking in fastest way. Dijkstra’s algorithm initials the paths to finding the shortest path while ACO optimizes the paths. …”
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3
Path planning for unmanned aerial vehicle (UAV) using rotated accelerated method in static outdoor environment
Published 2021“…In this study, a fast iterative method known as Rotated Successive Over-Relaxation (RSOR) is introduced. The algorithm is implemented in a self-developed 2D Java tool, UAV Planner. …”
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4
Smart appointment organizer for mobile application / Mohd Syafiq Adam
Published 2009“…The main component of this prototype is the use of Dijkstra algorithm to compute the shortest path from source of appointment to the 6 points of destinations within UiTM Shah Alam. …”
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5
Optimize the maximum flow of electricity capacity using Ford Fulkerson, Edmonds Karp and Goldberg Tarjan algorithm / Nik Nur Diyana Nik Mohd Huzaidi
Published 2024“…The main goals are to study these algorithms for maximum electricity flow, implement them to find the best flow in electricity transmission, and optimize the flow using these methods. …”
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6
Transmission loss and load flow allocations via genetic algorithm technique
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7
Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources
Published 2021“…In this research, a novel algorithm (Herschel Bulkley Network) is introduced to simulate the non-Newtonian fluid flow in a pipe using data redundant deep neural network (DNN) for fully developed, laminar, and incompressible flow conditions. …”
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Reduced Galloping Column Algorithm For Memory Testing
Published 2015“…There are lots of memory algorithms used for memory testing, including the galloping column algorithm (GalCol). …”
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9
Optimal placement and sizing of FACTS devices for optimal power flow using metaheuristic optimizers
Published 2022“…OPF is one of the well-known problems in power system operations and with the inclusion of the FACTS devices allocation problems into OPF will make the solution more complex. Thus, seven metaheuristic algorithms: Barnacles Mating Optimizer (BMO), Marine Predators Algorithm (MPA), Moth–Flame Optimization (MFO), Particle Swarm Optimization (PSO), Gravitational Search Algorithm (GSA), Teaching–Learning-Based Optimization (TLBO) and Heap-Based Optimizer (HBO) are used to solve two objective functions: power loss and cost minimizations. …”
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The Use of Artificial Neural Networks and Genetic Algorithms for Effectively Optimizing Production from Multiphase Flow Wells
Published 2010“…The need for accurate prediction of these parameters is a key factor in clearly understanding multiphase flow in tubing. Prediction of pressure drop in multiphase flow is quite difficult and complicated due to the complex relationships between the various parameters involved. …”
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Optimal power flow incorporating stochastic wind and solar generation by metaheuristic optimizers
Published 2021“…Optimal power flow (OPF) is one of the complex problems in power system operation that includes multi-modal, large-scale, non-convex and non-linear constrained optimization problems. …”
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12
Improving throughput of TCP flows by utilizing TCP-aware backpressure scheduling
Published 2023“…Backpressure algorithm is one of the techniques that can be used to achieve the maximum network throughput policies in wireless environments by routing the traffic over a multi-hop network dynamically using congestion gradient that directing the traffic around a queuing network. …”
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A trade-off criterion for bi-objective problem in solving hybrid flow shop scheduling with energy efficient (EE-HFS) using multi-objective dragonfly algorithm (MODA)
Published 2024“…The (EE-HFS) optimization has been carried out using the Multi-Objective Dragonfly Algorithm (MODA). …”
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14
An optical flow measurement technique based on continuous wavelet transform
Published 2018“…Flow measurement underwater oil leak is a challenging problem, due to the complex nature of flow dynamics. …”
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15
An optical flow measurement technique based on continuous wavelet transform
Published 2018“…Flow measurement underwater oil leak is a challenging problem, due to the complex nature of flow dynamics. …”
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16
Optimal power flow using hybrid firefly and particle swarm optimization algorithm
Published 2020“…In this paper, a novel, effective meta-heuristic, population-based Hybrid Firefly Particle Swarm Optimization (HFPSO) algorithm is applied to solve different non-linear and convex optimal power flow (OPF) problems. …”
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17
A novel Tiki-Taka algorithm to optimize hybrid flow shop scheduling with energy consumption
Published 2022“…This paper modeled and optimized HFS with energy consumption using Tiki-Taka Algorithm (TTA). TTA is a novel algorithm inspired by football playing style that focuses on short passing and player positioning. …”
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18
Hybrid flow shop scheduling problem with energy utilization using non-dominated sorting genetic algorithm-III (NSGA-III) optimization
Published 2023“…In the future, these multi-objective algorithms’ potential can be further investigated for hybrid flow shop scheduling problems.…”
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Optimal power flow solutions for power system operations using moth-flame optimization algorithm
Published 2021“…In this thesis, a recent metaheuristic nature-inspired optimization algorithm namely: Moth-Flame Optimizer (MFO) is applied to solve the two subproblems of Optimal power flow (OPF) namely: Economic dispatch (ED) and Optimal reactive power dispatch (ORPD) simultaneously. …”
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20
Parameter Estimation of Lorenz Attractor: A Combined Deep Neural Network and K-Means Clustering Approach
Published 2022“…DNN techniques is suitable in solving nonlinear and complex problem. The most popular method to solve parameter estimation problem is using optimization algorithm that easily trap to local minima and poor in exploitation to find the good solutions. …”
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