Search Results - (( based reactive process algorithm ) OR ( java application learning algorithm ))
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Optimization-based simulation algorithm for predictive-reactive job-shop scheduling of reconfigurable manufacturing systems
Published 2022“…Predictive-reactive strategy was investigated, in which Genetic Algorithm (GA) and dispatching rules were used for predictive scheduling and reactivity controls. …”
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Cuckoo search algorithm as an optimizer for optimal reactive power dispatch problems
Published 2017“…CSA is inspired by the parasitic behavior of Cuckoo birds in reproduction process based on the probability for a host bird in discovering an alien egg in its nest. …”
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Reactive approach for automating exploration and exploitation in ant colony optimization
Published 2016“…However, ACO-based reactive search technique has three (3) problems. …”
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An optimization approach for predictive-reactive job shop scheduling of reconfigurable manufacturing systems
Published 2022“…The predictive-reactive strategy was investigated, in which Genetic Algorithm (GA) and dispatching rules were used for predictive scheduling and reactivity controls. …”
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Development of behavior-based reactive navigation system for mobile robot
Published 2013“…To solve the problems and achieve the above objective, a new behavior-based reactive navigation system for mobile robots is developed. …”
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An Educational Tool Aimed at Learning Metaheuristics
Published 2020“…In this paper, we introduce an education tool for learning metaheuristic algorithms that allows displaying the convergence speed of the corresponding metaheuristic upon setting/changing the dependable parameters. …”
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A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The methodology used consists of theoretical study, design of formal framework on intelligent software quality, identification of Feature Ranking Technique (FRT), construction and evaluation of FRA algorithm. The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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Benchmark studies on Optimal Reactive Power Dispatch (ORPD) Based Multi-Objective Evolutionary Programming (MOEP) using Mutation Based on Adaptive Mutation Operator (AMO) and Polyn...
Published 2016“…Present days, Power System operates in a stressed condition due to reactive power shortage. Hence, this research involves development of an adaptive mutation algorithm based multi-objective for Optimal Reactive Power Dispatch (ORPD) in a power system in order to minimize the total loss and the improved voltage stability simultaneously. …”
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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde
Published 2022“…This thesis is based on the application of sentiment classification algorithm to tweet data with the goal of classifying messages based on the polarity of sentiment towards a particular topic (or subject matter). …”
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Novel techniques for voltage stability assessment and improvement in power system / Ismail Musirin.
Published 2004“…A new Evolutionary programming (EP) based acceleration search algorithm was developed to accelerate the process in estimating maximum load ability in a power system. …”
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Development Of Machine Learning User Interface For Pump Diagnostics
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Active and reactive power scheduling optimization using firefly algorithm to improve voltage stability under load demand variation
Published 2023“…This paper presents active and reactive power scheduling using firefly algorithm (FA) to improve voltage stability under load demand variation. …”
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AI powered asthma prediction towards treatment formulation: an android app approach
Published 2022“…TensorFlow is utilized to integrate machine learning with an Android application. We accomplished asthma therapy using an Android application developed in Java and running on the Android Studio platform.…”
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Unified strategy for intensification and diversification balance in ACO metaheuristic
Published 2017“…This intensification and diversification in Ant Colony Optimization (ACO) is the search strategy to achieve a trade-off between learning a new search experience (exploration) and earning from the previous experience (exploitation).The automation between the two processes is maintained using reactive search. However, existing works in ACO were limited either to the management of pheromone memory or to the adaptation of few parameters.This paper introduces the reactive ant colony optimization (RACO) strategy that sticks to the reactive way of automation using memory, diversity indication, and parameterization. …”
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AI powered asthma prediction towards treatment formulation : An android app approach
Published 2022“…TensorFlow is utilized to integrate machine learning with an Android application. We accomplished asthma therapy using an Android application developed in Java and running on the Android Studio platform.…”
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…Features selection process can be considered a problem of global combinatorial optimization in machine learning. Genetic algorithm GA had been adopted to perform features selection method; however, this method could not deliver an acceptable detection rate, lower accuracy, and higher false alarm rates. …”
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