Search Results - (( program indicator selection algorithm ) OR ( java segmentation mining algorithm ))
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Image clustering comparison of two color segmentation techniques
Published 2010“…Finally, the algorithm found, which would solve the image segmentation problem.…”
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Firefly algorithm for optimal sizing of Standalone Photovoltaic System / Nurizzati Abdul Aziz
Published 2016“…The sizing algorithm utilized Firefly Algorithm (FA) to optimally select the model of each system component such that a system technical performance indicator is consequently optimized. …”
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Firefly algorithm for optimal sizing of stand-alone photovoltaic system / Nur Izzati Abdul Aziz
Published 2016“…The sizing algorithm utilized Firefly Algorithm (FA) to optimally select the model of each system component such that a system technical performance indicator is consequently optimized. …”
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Optimizing tree planting areas through integer programming and improved genetic algorithm
Published 2012“…Therefore, a hybrid algorithm through an incorporation of Integer Programming and Improved Genetic Algorithm was proposed for planting lining design. …”
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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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Towards a better feature subset selection approach
Published 2010“…The selection of the optimal features subset and the classification has become an important issue in the data mining field.We propose a feature selection scheme based on slicing technique which was originally proposed for programming languages.The proposed approach called Case Slicing Technique (CST).Slicing means that we are interested in automatically obtaining that portion 'features' of the case responsible for specific parts of the solution of the case at hand.We show that our goal should be to eliminate the number of features by removing irrelevant once.Choosing a subset of the features may increase accuracy and reduce complexity of the acquired knowledge.Our experimental results indicate that the performance of CST as a method of feature subset selection is better than the performance of the other approaches which are RELIEF with Base Learning Algorithm (C4.5), RELIEF with K-Nearest Neighbour (K-NN), RELIEF with Induction of Decision Tree Algorithm (ID3) and RELIEF with Naïve Bayes (NB), which are mostly used in the feature selection task.…”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli
Published 2018“…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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Optimized placement, sizing, and selection of distributed generation using the salp swarm algorithm
Published 2025“…The salp swarm algorithm (SSA) was introduced as a method for efficiently selecting the optimal location, size, and type of distributed generation (DG) in a distribution system. …”
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A comparative study of multi-objective optimal power flow based on particle swarm, evolutionary programming, and genetic algorithm
Published 2015“…This paper compares the performance of three population-based algorithms including particle swarm optimization (PSO), evolutionary programming (EP), and genetic algorithm (GA) to solve the multi-objective optimal power flow (OPF) problem. …”
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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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Optimization Of Two-Dimensional Dual Beam Scanning System Using Genetic Algorithms
Published 2008“…The simulation results indicate that the algorithm is able to segregate and assign the tasks for each scanning head and also able to find the shortest scanning path for different types of objects coordination. …”
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Selection of prospective workers using profile matching algorithm on crowdsourcing platform
Published 2022“…This algorithm is able to select worker profiles from 10,000 datasets, up to 1148 people who are most suitable for the tasks offered. …”
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Predictive Analytics in Genetic Engineering as an Optimization Problem
Published 2024“…Also, the predictive outcomes of the computational simulation that was implemented in Python programming indicate that these local cultivars are developing drought-tolerant genetic variability. …”
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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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REDUCING LATENCY IN A VIRTUAL REALITY-BASED TRAINING APPLICATION
Published 2006“…Findings indicated that heuristic-based algorithm is an accurate prediction method to compensate latency in virtual training. …”
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Development of a software for simulating active force control schemes of a two-link planar manipulator
Published 2005“…On Top Of That, The Graphical Results Can Be Observed And Analysed On-Line While The Program Is Running. By Using Matlab And Its Gui Facility, All The AFC Schemes Already Described In The Previous Works Such As The AFC With Crude Approximation Method, AFC And Iterative Learning (Afcail), AFC And Neural Network (Afcann), AFC And Fuzzy Logic (Afcafl), And AFC And Genetic Algorithm (Afcaga) Schemes Were Linked Into A Single Menu-Driven Program Where Each Of The Scheme Can Be Easily Selected And Executed By The User. …”
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Comparison of Recursive Feature Elimination and Boruta as Feature Selection in Greenhouse Gas Emission Data Classification
Published 2024“…The results indicate that classification performance improves with feature selection and recursive feature elimination compared to scenarios without feature selection or with Boruta feature selection. …”
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A hybrid ANN for output power prediction and online monitoring in grid-connected photovoltaic system / Puteri Nor Ashikin Megat Yunus
Published 2023“…Improved Fast Evolutionary Programming (IFEP), Evolutionary Programming- Dolphin Echolocation Algorithm (EPDEA) and Evolutionary Programming-Firefly Algorithm (EPFA). …”
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A Multi-Criteria Decision-Making Approach for Targeted Distribution of Smart Indonesia Card (KIP) Scholarships
Published 2025“…Recipient selection also involves various factors, including poverty indicators, social conditions, and academic performance. …”
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