Search Results - (( developing issues control algorithm ) OR ( java implementation tree algorithm ))
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Study and Implementation of Data Mining in Urban Gardening
Published 2019“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…The method was implemented using Java and the results of the simulation were evaluated using five standard performance metrics: accuracy, AUC, precision, recall, and f-Measure. …”
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Embedded system for indoor guidance parking with Dijkstra’s algorithm and ant colony optimization
Published 2019“…This study proposes a car parking management system which applies Dijkstra’s algorithm, Ant Colony Optimization (ACO) and Binary Search Tree (BST) in structuring a guidance system for indoor parking. …”
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Implementation of generalized predictive control (GPC) for a real-time process control using labview
Published 2006“…Real-time issues such as rapid testing, nonlinearity and computational problem have led researchers in recent years to do intensive work on development methodologies to enhance control in real-time. …”
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Computing the autopilot control algorithm using predictive functional control for unstable model
Published 2009“…This paper discusses the computing development of a control algorithm using Predictive Functional Control (PFC) for model-based that having one or more unstable poles. …”
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A Survey on Distributed Topology Control Techniques for Extending the Lifetime of Battery Powered Wireless Sensor Networks
Published 2013“…First, we review the significant topology control algorithms to provide insights into how energy efficiency is achieved by design. …”
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Model Predictive Control Design for f Nonlinear Four-Tank System
Published 2008“…In this thesis, besides good performance, the algorithm enjoys from relative simplicity and faster response in compare with the algorithms developed in other previous works. …”
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Automatic generation of neural game controller using single and bi-objective evolutionary optimization algorithms for RTS Game
Published 2015“…In the last experiment, the results showed that DE and EP algorithms can generate superior controllers whilst PDE is only capable to generate sub-optimal controllers. …”
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Utility-based non-cooperative power control game in wireless environment / Yousef Ali Mohammed Al-Gumaei
Published 2017“…This thesis therefore addresses these issues by studying a theoretical framework for the design and analysis of distributed power control algorithms for modern cognitive radio and femtocell networks. …”
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Dynamic Feedback Flow Control Algorithms for Unicast and Multicast Available Bit Rate Service in Asynchronous Transfer Mode Networks
Published 2000“…This thesis develops dynamic feedback flow control schemes in ATM networks, with primary focus on point-to-point (unicast) and point-tomUltipoint (multicast) ABR algorithms. …”
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Experimental evaluation of bottleneck link utilization with new-additive increase multiplicative decrease congestion avoidance and control algorithm.
Published 2009“…And also all the developments for the congestion control and avoidance algorithms interest about the using of network resources and use the links capacity (utilization). …”
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An Optimized Binary Scheduling Controller for Microgrid Energy Management Considering Real Load Conditions
Published 2024“…To confirm the efficiency of the developed controller, a comparison is conducted between the results achieved with and without microgrid (MG) integration. …”
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Intelligent Evolutionary Controller for Flexible Robotic Arm
Published 2020“…This research focused on the development of the intelligent evolutionary controller algorithms for controlling flexible robotic arm manipulator. …”
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Optimization algorithms for energy storage integrated microgrid performance enhancement
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Iteration strategy and ts effect towards the performance of population based metaheuristics
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