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1
Teaching and learning via chatbots with immersive and machine learning capabilities
Published 2019“…These chatbots support learning of Java via problem-solving steps through “learning by doing”. …”
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2
Assessing the simulation performances of multiple model selection algorithm
Published 2015“…The capability of the algorithm in finding the true specification of multiple models is measured by the percentage of simulation outcomes.Overall results show that the algorithm has performed well for a model with two equations.The findings also indicated that the number of variables in the true models affect the algorithm performances. …”
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3
CAT CHAOTIC GENETIC ALGORITHM BASED TECHNIQUE AND HARDWARE PROTOTYPE FOR SHORT TERM ELECTRICAL LOAD FORECASTING
Published 2017“…ANN based STLF models commonly use back-propagation algorithm, which generally exhibits a slow and improper convergence that affects the forecast accuracy. …”
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4
The use of heuristic ordering and particle swarm optimization for nurse scheduling problem
Published 2017“…The comparison of the result of HOPSO, harmony search algorithm (HSA) and heuristic variable neighborhood search (HVNS) is presented. …”
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5
A review of crossover methods and problem representation of genetic algorithm in recent engineering applications
Published 2020“…GA has many variations such as real coded and binary coded depending on the problem representation and so affects the forms of genetic operators. When optimizing process variables, the efficiency of crossover method is crucial. …”
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Improvement on rooftop classification of worldview-3 imagery using object-based image analysis
Published 2019“…Furthermore, a systematic feature selection approach was proposed in which search algorithms (Ant-Search, Best First-Search and Particle Swamp Optimization (PSO) - Search) performance were evaluated to select the most significant features. …”
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7
Acoustic emission partial discharge localization in oil based on artificial bee colony
Published 2025“…It is known that localization algorithms are among the factors that can affect PD localization accuracy, and the ongoing research in this area underscores the need for further advancements in this topic. …”
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A Hybrid Adaptive Leadership GWO Optimization with Category Gradient Boosting on Decision Trees Algorithm for Credit Risk Control Classification
Published 2024“…This enhanced version of the Grey Wolf Optimization algorithm possesses robust global search capabilities and helps alleviate some of the local convergence issues inherent in the original GWO algorithm. …”
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9
Mathematical simulation for 3-dimensional temperature visualization on open source-based grid computing platform
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10
Optimization of medical image steganography using n-decomposition genetic algorithm
Published 2023“…To overcome these limitations, this study proposes a technique known as an n-decomposition genetic algorithm. This algorithm uses a variable-length search to identify the best location to embed the secret message by incorporating constraints to avoid local minimum traps. …”
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11
Solving large-scale problems using multi-swarm particle swarm approach
Published 2018“…The proposed approach strived to scale up the application of the (PSO) algorithm towards solving large-scale optimization tasks of up to 1000 real-valued variables. …”
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Adapting perturbation voltage for variable speed micro-hydro using particle swarm optimization (PSO)
Published 2022“…Results show that the value of perturbation speed affects the performance of MPPT algorithm to search the maximum operating point. …”
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13
A NOVEL FORWARD BACKWARD LINEAR PREDICTION ALGORITHM FOR SHORT TERM POWER LOAD FORECAST
Published 2010“…The proposed AR-based algorithm divides long data record into short segments and searches for the AR coefficients that simultaneously model the data with the least means squared errors. …”
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14
Mobile data gathering algorithms for wireless sensor networks
Published 2014“…In this algorithm, the user has to tune an appropriate variable which directly affects the power consumption and the data gathering latency. …”
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15
Solving SVM model selection problem using ACOR and IACOR
Published 2013“…In applying ACO for optimizing SVM parameters which are continuous variables, there is a need to discretize the continuously value into discrete values.This discretize process would result in loss of some information and hence affect the classification accuracy.In order to enhance SVM performance and solving the discretization problem, this study proposes two algorithms to optimize SVM parameters using Continuous ACO (ACOR) and Incremental Continuous Ant Colony Optimization (IACOR) without the need to discretize continuous value for SVM parameters.Eight datasets from UCI were used to evaluate the credibility of the proposed integrated algorithm in terms of classification accuracy and size of features subset.Promising results were obtained when compared to grid search technique, GA with feature chromosome-SVM, PSO-SVM, and GA-SVM. …”
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A hybrid sampling-based path planning algorithm for mobile robot navigation in unknown environments
Published 2013“…Finally, an adaptive neuro-fuzzy inference system (ANFIS) was designed which constructs and optimizes a fuzzy logic controller using a given dataset of input/output variables in order to increase the optimality and stability rates of the proposed path planning algorithm. …”
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17
Predicting crop yield and field energy output for oil palm using genetic algorithm and neural network models
Published 2019“…Finally, this research concluded that a genetic algorithm is useful for selecting input variables in oil palm production. …”
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18
Solving Support Vector Machine Model Selection Problem Using Continuous Ant Colony Optimization
Published 2013“…Ant Colony Optimization has been used to solve Support Vector Machine model selection problem.Ant Colony Optimization originally deals with discrete optimization problem.In applying Ant Colony Optimization for optimizing Support Vector Machine parameters which are continuous variables, there is a need to discretize the continuously value into discrete value.This discretize process would result in loss of some information and hence affect the classification accuracy and seeking time.This study proposes an algorithm that can optimize Support Vector Machine parameters using Continuous Ant Colony Optimization without the need to discretize continuous value for Support Vector Machine parameters.Eight datasets from UCI were used to evaluate the credibility of the proposed hybrid algorithm in terms of classification accuracy and size of features subset.Promising results were obtained when compared to grid search technique, GA with feature chromosome-SVM, PSO-SVM, and GA-SVM.…”
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Integrated face detection approach for far image application
Published 2016“…The last stage of the algorithm is to apply the Euler method, in which its function is to search for the facial features. …”
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20
Incremental continuous ant colony optimization technique for support vector machine model selection problem
Published 2012“…In applying Ant Colony Optimization for optimizing Support Vector Machine parameters which are continuous variables, there is a need to discretize the continuously value into discrete value.This discretize process would result in loss of some information and hence affect the classification accuracy and seeking time. …”
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