Search Results - (( java application using algorithm ) OR ( data selection ((_ algorithm) OR (based algorithm)) ))
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection
Published 2022“…Therefore, in this paper, we proposed Dynamic tasks scheduling algorithm based on attribute reduction with an enhanced hybrid Genetic Algorithm and Particle Swarm Optimization for optimal device selection. …”
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2
A Feature Ranking Algorithm in Pragmatic Quality Factor Model for Software Quality Assessment
Published 2013“…The assessment of quality attributes has been improved using FRA algorithm enriched with a formula to calculate the priority of attributes and followed by learning adaptation through Java Library for Multi Label Learning (MULAN) application. …”
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3
Campus safe: Safeguarding GPS-based Physical Identity and Access Management (PIAM) system with a lightweight Geo-Encryption
Published 2022“…The selected lightweight geo-encryption algorithm will be implemented in the proposed system, vi which develops by using Java language. …”
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4
Features selection for intrusion detection system using hybridize PSO-SVM
Published 2016“…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
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5
A malware analysis and detection system for mobile devices / Ali Feizollah
Published 2017“…We then used feature selection algorithms and deep learning algorithms to build a detection model. …”
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6
Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection
Published 2008“…Sequential pattern mining is a new branch of data, mining science that solves inter-transaction pattern mining problems. …”
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7
Case Slicing Technique for Feature Selection
Published 2004“…CST was compared to other selected classification methods based on feature subset selection such as Induction of Decision Tree Algorithm (ID3), Base Learning Algorithm K-Nearest Nighbour Algorithm (k-NN) and NaYve Bay~sA lgorithm (NB). …”
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8
Artificial immune system based on real valued negative selection algorithms for anomaly detection
Published 2015“…The Real-Valued Negative Selection Algorithms, which are the focal point of this research, generate their detector sets based on the points of self data. …”
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9
Improved Salp Swarm Algorithm based on opposition based learning and novel local search algorithm for feature selection
Published 2020“…An improved version of Salp Swarm Algorithm (ISSA) is proposed in this study to solve feature selection problems and select the optimal subset of features in wrapper-mode. …”
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10
Enhancing Classification Algorithms with Metaheuristic Technique
Published 2024“…Classification is a process of grouping or placing data into appropriate categories or classes based on specificattributes or features to predict labels or classes of new data based on patternsobserved from previously trained data. …”
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Static and self-scalable filter range selection algorithms for peer-to-peer networks
Published 2011“…Two multiple selection algorithm, which are known as “static filter range selection algorithm” and “self-scalable selection algorithm” are proposed. …”
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12
Mutable composite firefly algorithm for gene selection in microarray based cancer classification
Published 2022“…Hence, this study proposed to modify the Firefly Algorithm (FA) along with the Correlation-based Feature Selection (CFS) filter for the gene selection task. …”
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13
Reducing of Inconsistent Data using Fuzzy Multi Attribute Decision Making for Accessing Data from Database
Published 2013“…This technique contains 5 steps which are deriving quality vector, scale the quality matrix, compute weighted Euclidean distance and select final alternative. An application was developed using java and oracle technology. …”
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Melanoma skin cancer recognition using negative selection algorithm / Muhammad Rushamir Hakimi Ruslan
Published 2017“…This study has shown how the Negative Selection Algorithm can diagnose the skin cancer based on the input image and extracted data that has been provided. …”
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15
Improving Classification of Remotely Sensed Data Using Best Band Selection Index and Cluster Labelling Algorithms
Published 2005“…In cluster generating process, the developed BBSI algorithm was used to select the best band combination for generating cluster by using Iterative self- Organizing Data Analysis (ISODATA) technique. …”
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16
An ensemble learning method for spam email detection system based on metaheuristic algorithms
Published 2015“…In the second phase, a classifier ensemble learning model is proposed consisting of separate outputs: (i) To select a relevant subset of original features based on Binary Quantum Gravitational Search Algorithm (QBGSA), (ii) To mine data streams using various data chunks and overcome a failure of single classifiers based on SVM, MLP and K-NN algorithms. …”
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17
AGENT MEETING SCHEDULER
Published 2011“…An agent meeting scheduler prototype then will be developed to prove that the selected algorithm is working properly. Qualitative research method is being used to gather necessary data on agent algorithm and this data will be used to select the suitable algorithm. …”
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Enhancement of bearing defect diagnosis via genetic algorithm optimized feature selection
Published 2015“…In addition, GA has the limitation on generalization which causes the problem of overfitting to the training data. Therefore a correlation-based filtering algorithm is embedded into GA feature selection to solve the over-fitting problem and increase the adaptability of the diagnostic scheme to unpredictable input data. …”
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19
Mobile data gathering algorithms for wireless sensor networks
Published 2014“…In this research, a Mobile Data Gathering based Network Layout (MDG-NL) algorithm is proposed. …”
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20
SURE-Autometrics algorithm for model selection in multiple equations
Published 2016“…The SURE-Autometrics is also validated using two sets of real data by comparing the forecast error measures with five model selection algorithms and three non-algorithm procedures. …”
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