Search Results - (( framework implementation case algorithm ) OR ( java data optimization algorithm ))

Using GA and KMP algorithm to implement an approach to learning through intelligent framework documentation by Mat Jani H., Lee S.P.

“…The main objective of this paper is to propose and implement an intelligent framework documentation approach that integrates case-based learning (CBL) with genetic algorithm (GA) and Knuth-Morris-Pratt (KMP) pattern matching algorithm with the intention of making learning a framework more effective. …”

Implementing case-based reasoning approach to framework documentation by Hajar M.J., Lee S.P.

“…This paper discusses and implements the case-based reasoning (CBR) approach to documenting a framework. …”

Fuzzy modeling using Bat Algorithm optimization for classification by Noor Amidah, Ahmad Sultan

“…A Sazonov Engine which is a fuzzy java engine is use to apply Bat Algorithm in the experiment. …”
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Attribute reduction based scheduling algorithm with enhanced hybrid genetic algorithm and particle swarm optimization for optimal device selection by Nwogbaga, Nweso Emmanuel, Latip, Rohaya, Affendey, Lilly Suriani, Abdul Rahiman, Amir Rizaan

“…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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Low-level hybridization scripting language with dynamic parameterization in PSO-GA / Suraya Masrom by Masrom, Suraya

“…However, in many cases, implementing the suitable hybrid algorithms for a given optimization problem is a considerably difficult, which in most cases, is time consuming. …”
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Quantum Processing Framework And Hybrid Algorithms For Routing Problems by Soltan Aghaei, Mohammad Reza

“…The framework is used to increase the implementation performance of quantum algorithms. …”
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A test case generation framework based on UML statechart diagram by Salman, Yasir Dawood

“…The results of the experts’ review show that the framework is practical, easy to implement due to it is suitability to generate the test cases. …”
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An improved diabetes risk prediction framework : An Indonesian case study by Sutanto, Daniel Hartono

“…However,there is the issue of noisy dataset detected as incomplete data and the outlier class problem that affects sampling bias.Existing frameworks were deemed difficult in identifying the critical risk factors of diabetes;some of which were considerably inaccurate and consume substantial computation time.The purpose of this study is to develop a suitable framework for predicting diabetes risks.From a complete blood test,the framework can predict and classify the output of either having diabetes risk or no diabetes risk.A Diabetes Risk Prediction Framework (DRPF) was developed from the literature review and case studies were afterwards conducted in three private hospitals in Semarang.Analyses were conducted to find a suitable component of the framework—due to lack of comparison and analysis on the combination of feature selection and classification algorithm.DRPF comprises four main sections: pre-processing,outlier detection,risk weighting,and learning. …”
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A random search based effective algorithm for pairwise test data generation by Sabira, Khatun, K. F., Rabbi, Che Yahaya, Yaakub, Klaib, Mohammad F. J.

“…This paper proposes an effective random search based pairwise test data generation algorithm named R2Way to optimize the number of test cases. …”
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Scalable approach for mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

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EasyA: Easy and effective way to generate pairwise test data by Rabbi, Khandakar Fazley, Sabira, Khatun, Che Yahaya, Yaakub, Klaib, Mohammad F. J.

“…This paper proposes a matrix based calculation for pairwise test data generation algorithm named EasyA to optimize the number of test cases. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…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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Low-level hybridization scripting language with dynamic parameterization in PSO-GA / Suraya Masrom by Masrom, Suraya

“…However, in many cases, implementing the suitable hybrid algorithms for a given optimization problem is a considerably difficult, which in most cases, is time consuming. …”
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Manufacturing process planning optimisation in reconfigurable multiple parts flow lines by Ismail, Napsiah, Musharavati, Farayi, Hamouda, Abdel Magid Salem, Ramli, Abdul Rahman

“…Design/methodology/approach: The genetic algorithm methodology implements a genetic algorithm that is augmented by application specific heuristics in order to guide the search for an optimal solution. …”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Enhanced bibliographic data retrieval and visualization using query optimization and spectral centrality measure by Ramasamy, Chitra, Zolkepli, Maslina

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A new framework for geospatial site selection using artificial neural networks as decision rules: a Case study on landfill sites by Abujayyab, Sohaib K. M., Ahamad, Mohd Anusi S., Yahya, Ahmad Shukri, H. Y. Saad, Abdul Malik

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Audio Streaming System Using Real-Time Transport Protocol Based on Java Media Framework by Asaad Aref, Ibrahim

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Error concealment technique using wavelet neural network for wireless transmitted digital images by Al-Azzawi, Alaa Khamees

“…In the case, where the missing regions of pixels are containing textures, edges, and other image features that are not easily handled by concealment algorithms. …”
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Flexible window-based scheduling with critical worst case latency evaluations for real time traffic in time sensitive networks by Muftah, Shalghum Khaled

“…The first part introduces a flexible window-overlapping scheduling (FWOS) algorithm that allows the TT windows to overlap in GCL implementations. …”
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