Search Results - (( java implementation path algorithm ) OR ( cooling system using algorithm ))
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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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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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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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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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Development Of Control Algorithm For Spot Cooling System
Published 2017“…This project’s aim is to develop a Control Algorithm for Spot Cooling system. The system helps to detect and track a non-human decoy. …”
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Monograph -
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Neural Network-Based Active Cooling System With IoT Monitoring and Control for LCPV Silicon Solar Cells
Published 2024“…The simulation of the cooling system operation was performed using various algorithms of the cooling system operation. …”
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An application of a novel technique for assessing the operating performance of existing cooling systems on a university campus
Published 2018“…Two contributions in this work are: (1) the prediction of a model by using Adaptive Neuro-Fuzzy Inference System (ANFIS)-based Fuzzy Clustering Subtractive (FCS), and (2) the classification and optimization of the predicted models by using an Accelerated Particle Swarm Optimization (APSO) algorithm. …”
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Investigation of maximum power point tracking (MPPT) for active cooling mono-crystalline photovoltaic panel using fuzzy logic controller
Published 2017“…To achieve the maximum power point (MPP) of PV panel, fuzzy logic (FL) based constant voltage (CV) algorithm is applied to the system. The aim of this project is to develop an efficient standalone PV system with cooling system. …”
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9
Development of a building energy analysis package (BEAP) and its application to the analysis of cool thermal energy storage systems
Published 2001“…Algorithms are developed for simulation of six generic cool thermal energy storage (CTES) systems. …”
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Optimization of HVAC system energy consumption in a building using artificial neural network and multi-objective genetic algorithm
Published 2023“…Air conditioning; Buildings; Cooling systems; Decision making; Energy conservation; Energy utilization; Genetic algorithms; Multiobjective optimization; Neural networks; Thermal comfort; Annual energy consumption; Building energy consumption; Building parameters; Dedicated outdoor air systems; Multi-objective genetic algorithm; Objective functions; Passive solar design; Radiant cooling; HVAC; air conditioning; artificial neural network; building; cooling; energy use; genetic algorithm; optimization; temperature effect…”
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Integrated cooling systems and maximum power point tracking of fuzzy logic controller for improving photovoltaic performances
Published 2019“…A method based on experimental study is developed to maximize the output of the PV panels using the combination of PV cooling system and fuzzy logic, fuzzy logic (FL)-based constant voltage (CV) maximum power point tracking (MPPT) algorithm. …”
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INCENTIVE-SCHEDULING ALGORITHMS TO PROVIDE GREEN COMPUTATIONAL DATA CENTER
Published 2017“…Accordingly, power supply for cooling such systems in a DC is up until 40% to 50% of the total power consumption. …”
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Correlation analysis and predictive performance based on KNN and decision tree with augmented reality for nuclear primary cooling process / Ahmad Azhari Mohamad Nor
Published 2024“…The intricate nature of these systems demands a well-managed maintenance program, prompting the need for a comprehensive characterisation of the primary cooling system. …”
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Algorithm development for optimization of a refrigeration system
Published 2010“…By using the Statistica software the new algorithm was generate by using linear regression analysis and the algorithm defined as γ = 4.284109 - 0.057164 χR from the algorithm and the international domestic refrigerator using R-134a COP value, was showed that the optimum charge for the refrigerator system occur at 31.21psi.R…”
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Evaluating power efficient algorithms for efficiency and carbon emissions in cloud data centers: a review
Published 2015“…To minimize the power wasted by data center cooling systems is directly related to data center location and climate change. …”
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Lithium Ion Battery Thermal Management System Using Optimized Fuzzy Controller
Published 2023Conference Paper -
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Design and Implementation of PID Controller for the Cooling Tower?s pH Regulation Based on Particle Swarm Optimization PSO Algorithm
Published 2025“…The methodology is to calculate the transfer function of the PH loop using the system identification toolbox of MATLAB, to design and implement a PID controller, to optimize the PID controller response using particle swarm optimization PSO algorithm, and to make a comparison among several tuning methods such as Ziegler Nichols (ZN) tuning method, MATLAB tuner method, and PSO algorithm tuning method. …”
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Optimizing crystal size distribution based on different cooling strategies in batch crystallization process
Published 2024“…The crystallization process was developed and simulated in Matlab software using a potash alum in the water system. Four optimization algorithms were proposed with different objective functions, such as maximizing mean crystal size (I), minimizing coefficient of variation (II), minimizing nucleus-grown crystals (III), and maximizing CSD (IV). …”
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