Search Results - (( weight selection process algorithm ) OR ( java implication tree algorithm ))
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Feature selection to enhance android malware detection using modified term frequency-inverse document frequency (MTF-IDF)
Published 2019“…The related best features in the sample are selected using weight and priority ranking process using K-means. …”
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A partition based feature selection approach for mixed data clustering / Ashish Dutt
Published 2020“…The proposed approach exploits the pre-processing nature of the partition clustering algorithm in the selection of weight assignment for nominal features. …”
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Evaluation of feature selection algorithm for android malware detection
Published 2018“…The related best features in the sample are selected using weight and priority ranking process. …”
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Self organizing multi-objective optimization problem
Published 2011“…The SOGA involves GA within GA evaluation process which optimally tunes the weight of each objective function and applies weighted-sum approach for fitness evaluation process. …”
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Development Of Stereo-Matching Algorithm Based On Adaptive Weighted Prediction
Published 2019“…The experimental result on the proposed algorithm is able to reduce 17.4% of weighted average error for all and 9.62% of weighted average error for nonocc (nonoccluded) compared to others Stereo Matching Algorithm without the proposed framework. …”
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Input significance analysis: Feature selection through synaptic weights manipulation for EFuNNs classifier
Published 2017“…As in the previous work, this work is particularly interested in ISA methods that can manipulate synaptic weights; namely Connection Weights (CW) and Garson’s Algorithm (GA), and the classifier selected is Evolving Fuzzy Neural Networks (EFuNNs). …”
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Fuzzy clustering method and evaluation based on multi criteria decision making technique
Published 2018“…A similar degree between points was utilized to get similarity density, and then by means of maximum density points selecting them as weights of the Kohonen algorithm. …”
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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“…All evaluation studies for MaOO algorithms have ignored to assign such weight for the target criteria during evaluation process. …”
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Optimisation of neural network with simultaneous feature selection and network prunning using evolutionary algorithm
Published 2015“…In this research work, a simultaneous feature reduction, network pruning and weight/biases selection is presented using fitness function design which penalizes selection of large feature sets. …”
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A New Co-Evolution Binary Particle Swarm Optimization With Multiple Inertia Weight Strategy For Feature Selection
Published 2019“…Feature selection is a task of choosing the best combination of potential features that best describes the target concept during a classification process. …”
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A proposed de-noising algorithm
Published 2020“…The algorithm did that by selecting a window measuring 3x3 as the center of processing pixels, other algorithms did that by using median filter (MF), adopted median filter (AMF), adopted weighted filter (AWF), and the adopted weighted median filter (AWMF). …”
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Hybrid Artificial Bees Colony algorithms for optimizing carbon nanotubes characteristics
Published 2018“…Optimization is a crucial process to select the best parameters in single and multi-objective problems for manufacturing process.However,it is difficult to find an optimization algorithm that obtain the global optimum for every optimization problem.Artificial Bees Colony (ABC) is a well-known swarm intelligence algorithm in solving optimization problems.It has noticeably shown better performance compared to the state-of-art algorithms.This study proposes a novel hybrid ABC algorithm with β-Hill Climbing (βHC) technique (ABC-βHC) in order to enhance the exploitation and exploration process of the ABC in optimizing carbon nanotubes (CNTs) characteristics.CNTs are widely used in electronic and mechanical products due to its fascinating material with extraordinary mechanical,thermal,physical and electrical properties. …”
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Condition diagnosis of bearing system using multiple classifiers of ANNs and adaptive probabilities in genetic algorithms
Published 2014“…Artificial Neural Networks (ANNs) are one of the most popular methods for classification in condition diagnosis of bearing systems.Regarding to ANNs performance, ANNs parameters have important role especially connectivity weights.In several running of learning processes with the same structure of ANNs, we can obtain different accuracy significantly since initial weights are selected randomly. …”
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Inertia weight strategies in GbLN-PSO for optimum solution
Published 2023“…In the PSO algorithm, inertia weight is an important parameter to determine the searching ability of each particle. …”
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An improved diabetes risk prediction framework : An Indonesian case study
Published 2018“…Pre-processing resolves the issue of missing data and hence normalizes the data.Outlier treatment employs k-mean clustering to validate the class.Suitable components were selected through comparison of classifier algorithms and feature selection.Attribute weighting based feature selection was selected for assigning weightage.Weighted risk factor was used on training dataset in order to improve accuracy and computation time of the prediction. …”
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An integrated algorithm of analytical network process with case-based reasoning to support the selection of an ideal football team formation and players
Published 2021“…However, there are very few algorithms or decision engines available that could actually be used by decision-makers to aid in the process of forming a football team. …”
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Adaptive-model based self-tuning generalized predictive control of a biodiesel reactor / Ho Yong Kuen
Published 2011“…Several RLS algorithms were screened and the Variable Forgetting Factor Recursive Least Squares (VFF-RLS) algorithm was selected to capture the dynamics of the process online for the purpose of model adaptation in the controller. …”
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A new standardisation and selection framework for real-time image dehazing algorithms from multi-foggy scenes based on fuzzy Delphi and hybrid multi-criteria decision analysis meth...
Published 2020“…Given the rapid development of dehazing image algorithms, selecting the optimal algorithm based on multiple criteria is crucial in determining the efficiency of an algorithm. …”
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