Search Results - (( development methodology optimizing algorithm ) OR ( java feature classification algorithm ))
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An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In order to address the challenges that mentioned above in this study, in the first phase, a novel architecture based on ensemble feature selection techniques include Modified Binary Bat Algorithm (NBBA), Binary Quantum Particle Swarm Optimization (QBPSO) Algorithm and Binary Quantum Gravita tional Search Algorithm (QBGSA) is hybridized with the Multi-layer Perceptron (MLP) classifier in order to select relevant feature subsets and improve classification accuracy. …”
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A multi-filter feature selection in detecting distributed denial-of-service attack
Published 2019“…It consists of 3-stage procedures: feature ranking, feature selection and classification. …”
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Conference or Workshop Item -
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Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…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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Software metrics selection model for predicting maintainability of object-oriented software using genetic algorithms
Published 2016“…The study proposes the use of software metric thresholds in the classification process during the GA representation. …”
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Estimation of photovoltaic models using an enhanced Henry gas solubility optimization algorithm with first-order adaptive damping Berndt-Hall-Hall-Hausman method
Published 2024“…The existing literature extensively explores the utilization of powerful Metaheuristic Algorithms (MAs) to address the complex constrained optimization problem in PV systems and achieve optimal solutions. …”
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Product assembly and disassembly sequence optimization based on genetic algorithm and design for assembly methodologies
Published 2009“…In this paper, an Artificial Intelligence (AI) technique, namely Genetic Algorithm (GA) is proposed to optimize product components assembly and disassembly sequences.The proposed methodology is developed and tested on an industrial product made of plastics with no integrated assembly and permanent joint parts.GA method is applied to determine the accuracy and optimum results based on 20 assembly and disassembly sequence solutions that was generated by the Design for Assembly methodology.The results indicated that GA based approach is able to obtain a near optimal solution for assembly and disassembly sequences.…”
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Conference or Workshop Item -
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Development Of Machine Learning User Interface For Pump Diagnostics
Published 2022“…The data collected for this machine learning model is using the statistically significant features from vibration and acoustic analysis. The features extracted of time domain and frequency domain in vibration and acoustic will use as database of a Support Vector Machine (SVM) algorithms by using MATLAB R2021a. …”
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Genetic algorithm optimization of product design for environmental impact reduction / Julirose Gonzales
Published 2018“…A novel feature-based product design methodology based on an integrated CAD-LCA approach is developed which analyzes a product design’s environmental impact. …”
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Application of response surface methodology coupled with genetic algorithm in the optimization of cutting conditions for surface roughness in end-milling of Inconel 718 using coate...
Published 2007“…This paper presents an efficient method of optimisation of surface roughness in end milling of Inconel 718 using TiAlN coated inserts under dry conditions by coupling response surface methodology (RSM) with genetic algorithm (GA). RSM has been utilized to develop an efficient mathematical model for surface roughness in terms of cutting parameters. …”
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Proceeding Paper -
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Hybridization of nonlinear sine cosine and safe experimentation dynamics algorithms for solving control engineering optimization problems
Published 2024“…The empirical assessment of these proposed methods encompasses a diverse set of 23 benchmark functions, demonstrating their efficacy comparable to well-established metaheuristic algorithms such as as the Grey Wolf Optimizer (GWO), Multi-Verse Optimization (MVO), Sine Cosine Algorithm (SCA), Ant Lion Optimizer (ALO), Moth-Flame Optimization Algorithm (MFO), and Grasshopper Optimization Algorithm (GOA). …”
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Hybrid 2D phase unwrapping methodology using spatial fuzzy clustering and neurofuzzy classification with application in sar images
Published 2001“…Existing phase unwrapping (PU) methodology has arbitrary settings in selection of most optimal algorithm for a particular phase image. …”
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Customised fitness function of evolutionary algorithm for optimization of car park space / Ahmad Syahir Ab. Aziz
Published 2017“…Genetic algorithm is chosen for the development of the prototype to prove that genetic algorithm is the best technique to implement for optimization. …”
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Cutting temperature and surface roughness optimization in CNC end milling using multi objective genetic algorithm
Published 2012“…Machining of hard materials at high cutting speeds produces high temperatures in the cutting zone, which affects the surface quality. Thus, developing a model for estimating the cutting parameters and optimizing this model to minimize the cutting temperatures and surface roughness becomes utmost important to avoid any damage to the quality surface.This paper presents the development of new models and optimizing these models of machining parameters to minimize the cutting temperature in end milling process by integrating the genetic algorithm (GA) with the statistical approach. …”
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Proceeding Paper -
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Methodology to develop heuristic for re-entrant flow shop with two potential dominant machines using bottleneck approach
Published 2012“…Two generalised makespan algorithms using bottleneck approach were developed for the identified bottleneck. …”
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Intelligent energy systems using the barnacles mating optimizer and evolutionary mating algorithm: Foundations, methods, and applications
Published 2026“…Intelligent Energy Systems using the Barnacles Mating Optimizer and Evolutionary Mating Algorithm: Foundations, Methods, and Applications reveals the potential of innovative optimization algorithms to support sustainability in modern energy systems. …”
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Book -
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Standardizing and weighting the evaluation criteria of many-objective optimization competition algorithms based on fuzzy delphi and fuzzy-weighted zero-inconsistency methods
Published 2021“…The evaluation criteria of Many Objective Optimization algorithm (MaOO) play a critical role in evaluating the competition MaOO algorithms. …”
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Landslide Susceptibility Mapping with Stacking Ensemble Machine Learning
Published 2024Conference Paper
