Search Results - (( program during selection algorithm ) OR ( java adaptation optimization algorithm ))
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Parallel distributed genetic algorithm development based on microcontrollers framework
Published 2023Conference paper -
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Some metaheuristic algorithms for solving multiple cross-functional team selection problems
Published 2022“…We introduced a method that combines a compromise programming (CP) approach and metaheuristic algorithms, including the genetic algorithm (GA) and ant colony optimization (ACO), to solve the proposed optimization problem. …”
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Software regression test case prioritization for object-oriented programs using genetic algorithm with reduced-fitness severity
Published 2015“…The re-execution of all test cases during the regression testing is costly. And even though several of the code based addresses procedural programs. …”
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4
A regression test case selection and prioritization for object-oriented programs using dependency graph and genetic algorithm
Published 2014“…This paper presents an evolutionary regression test case prioritization for object-oriented software based on dependence graph model analysis of the affected program using Genetic Algorithm. The approach is based on optimization of selected test case from test suite T. …”
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Development of dynamic programming algorithm for maintenance scheduling problem
Published 2020“…Using the dynamic programming algorithm developed, the model was also able to recalculate alternative schedules by replacing unavailable teams with other teams to avoid delays. …”
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Software metrics selection model for predicting maintainability of object-oriented software using genetic algorithms
Published 2016“…The latest effort to solve this selection problem is the development of the metrics selection model that uses genetic algorithm (GA). …”
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Smart energy meter with adaptive communication data transfer algorithm for electrical energy monitoring
Published 2021“…The prototype is constructed through software and hardware development and has been programmed using Arduino IDE software. An algorithm for selecting communication system is developed by comparing Received Signal Strength Indicator (RSSI) of Wi-Fi and GSM with the priority given to Wi-Fi, followed by GSM and RF. …”
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9
Regression test case selection & prioritization using dependence graph and genetic algorithm
Published 2014“…Unfortunately, it is costly and time consuming to allow for the re-execution of all test cases during regression testing. The challenge in regression testing is the selection of best test cases from the existing test suite.This paper presents an evolutionary regression test case prioritization for object-oriented software based on extended system dependence graph model of the affected program using genetic algorithm. …”
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The first task is to introduce a new rough model for minimum reduct selection and default rules generation, which is known as a Twofold Integer Programming (TIP). …”
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Flowshop scheduling using artificial bee colony (ABC) algorithm with varying onlooker bees approaches
Published 2015“…The main objective of this research is to develop a computer program with capability of manipulating the onlooker bee approaches in ABC Algorithm for solving flowshop scheduling problem. …”
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12
Cognitive selection mechanism performance in IEEE 802.11 WLAN
Published 2013“…The results for the selection were evaluated respectively to see the variation in selection pattern when compared to the default selection algorithm. …”
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A Community-Based Fault Isolation Approach for Effective Simultaneous Localization of Faults
Published 2019“…During program testing, software programs may be discovered to contain multiple faults. …”
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Anfis Modelling On Diabetic Ketoacidosis For Unrestricted Food Intake Conditions
Published 2017“…The project has also implemented the optimization process onto the proposed ANFIS model through the hybrid of Genetic Algorithm on the fuzzy membership function of the ANFIS model. …”
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15
A Simulated Annealing Approach to Solve Fuzzy Multi-Objective Linear Model for Supplier Selection in a Supply Chain
Published 2010“…At the same time due to the presence of vague and imprecise input parameters, makes the supplier selection complicated. During this project a fuzzy Multi-objective linear model is developed to achieve three important goals: Cost minimization, Quality maximization and Service level maximization and further it is converted into crisp single objective programming model using membership functions of the three objectives. …”
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Development of Machine Learning Algorithm for Acquiring Machining Data in Turning Process
Published 2004“…Artificial Neural Network (ANN) was selected from Machine Learning Algorithms to be the learning algorithm. …”
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Implementation of Health Monitoring System for Patients using Machine Learning Algorithms
Published 2024“…We employed the Decision Tree Algorithm to train and assess a model that produced a perfection of 66.66%.…”
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Performance and evaluation of soft handover system towards WCDMA in 3G network / Norlia Ghazali
Published 2004“…The results can be used to gain insight and help select the appropriate handover thresholds. Matlab is used as the programming language and to display the results.…”
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19
An Environmentally Energy Dispatch Using New Meta Heuristic Evolutionary Programming
Published 2018“…Basically,one important issue in the power system network is to provide the optimal Economic Load Dispatch (ELD) solution in order to guarantee the sustainable consumer load demand.However,today ELD solution is essential to include together with the environmental aspect and known as Environmental Economic Load Dispatch (EELD).For that reason, many researchers continue in the development of new simulation tool specifically to overcome the EELD problems.Therefore,this study prepared an improved hybrid metaheuristic technique named as New Meta Heuristic Evolutionary Programming (NMEP) to provide the best possible solution in solving the identified single objective and multi objective functions for EELD solution.This new technique a merging cloning strategy that involved in an Artificial Immune System (AIS) algorithm into algorithm of Meta Heuristic Evolutionary Programming (Meta-EP).The development of NMEP technique is to minimize total cost,reduce the total emission during generator operation through the common formula in EELD and lowest total system loss.Besides that,all mentioned objective functions were also optimized together simultaneously that formulated using the weighted sum method before had been executed on the multi objective NMEP or called MONMEP.Both individual and multi objective NMEP techniques performance were verified among other two common heuristic methods known as AIS and Meta-EP techniques.In addition,the best possible solution defined using the aggregate function method.Through this method,the selection of the best MOEELD solution became effortless as compared with MO individually that required compare two or more objective function in one time manually.Among those three optimization techniques the lowest total aggregate values mostly resulted via the NMEP technique.Based upon that,the proposed technique is proving as the outstanding method compared with Meta-EP and AIS techniques in solving the EELD problem for both standard IEEE 26 bus and 57 bus systems.…”
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