Search Results - (( java web selection algorithm ) OR ( program solution mining algorithm ))

Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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Measuring GPU-accelerated parallel SVM performance using large datasets for multi-class machine learning problem by Sulaiman M.A.H.B., Suliman A., Ahmad A.R.

Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif by Jantan, Hamidah, Mat Yusof, Norazmah, Abdul Latif, Mohd Hanapi

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A multi-filter feature selection in detecting distributed denial-of-service attack by Yon, Yi Jun, Leau, Yu-Beng, Suraya Alias, Park, Yong Jin

“…It consists of 3-stage procedures: feature ranking, feature selection and classification. Subsequently, an experimental evaluation of the proposed Multi-Filter Feature Selection (M2FS) method is performed by using the benchmark dataset, NSL-KDD and employed the J48 classification algorithm. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

“…But the large number of available prevention techniques make the selection of the best solution a big challenge, because not every technique fit all types of web application, hence a one technique for all is another issue and a difficult task. …”
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Towards a better feature subset selection approach by Shiba, Omar A. A.

“…The selection of the optimal features subset and the classification has become an important issue in the data mining field.We propose a feature selection scheme based on slicing technique which was originally proposed for programming languages.The proposed approach called Case Slicing Technique (CST).Slicing means that we are interested in automatically obtaining that portion 'features' of the case responsible for specific parts of the solution of the case at hand.We show that our goal should be to eliminate the number of features by removing irrelevant once.Choosing a subset of the features may increase accuracy and reduce complexity of the acquired knowledge.Our experimental results indicate that the performance of CST as a method of feature subset selection is better than the performance of the other approaches which are RELIEF with Base Learning Algorithm (C4.5), RELIEF with K-Nearest Neighbour (K-NN), RELIEF with Induction of Decision Tree Algorithm (ID3) and RELIEF with Naïve Bayes (NB), which are mostly used in the feature selection task.…”
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Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…To assess the applicability and accuracy of the proposed method for long-term electrical energy consumption, its estimates are compared with those obtained from artificial neural network (ANN), support vector regression (SVR), adaptive neuro-fuzzy inference system (ANFIS), rule-based data mining algorithm, GEP, linear, quadratic and exponential models optimized by particle swarm optimization (PSO), cuckoo search algorithm (CSA), artificial cooperative search (ACS) algorithm and backtracking search algorithm (BSA). …”
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Problem restructuring in interger programming for reduct searching by Ungku Chulan, Ungku Azmi Iskandar

“…In effect, they are very useful in generating rules when solving the classification problem that is inherent in data mining. The thesis emphasizes mainly on the improvement of the original SIP/DRIP algorithm in term of performance. …”
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Web page design for electronic commerce / Lee Fong Wai by Lee , Fong Wai

“…The sixth part covers the system implementation that involved the transformation of modules and algorithm into implementable commands by using the specified programming languages. …”
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Classification models for higher learning scholarship award decisions by Wirawati Dewi Ahmad, Azuraliza Abu Bakar

“…In this study, a data mining approach was used to propose a classification model of scholarship award result determination. …”
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Campus safe: Safeguarding GPS-based Physical Identity and Access Management (PIAM) system with a lightweight Geo-Encryption by Yeo Zi Zian

“…Literature review and experiment aimed to select the fastest lightweight geo-encryption algorithms and the smallest ciphertext and key size. …”
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Smart student timetable planner by Wong, Xin Tong

“…The system is implemented using Node.js with Express for server-side development, HTML, CSS, and JavaScript for the frontend, and Socket.IO for real-time collaboration. …”
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Dynamic and adaptive execution models for data stream mining applications in mobile edge cloud computing systems / Muhammad Habib Ur Rehman by Muhammad Habib , Ur Rehman

“…At application level, the program components need to handle continuously streaming data in order to perform knowledge discovery operations. …”
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K Nearest Neighbor Joins And Mapreduce Process Enforcement For The Cluster Of Data Sets In Bigdata by Md Shah, Wahidah, Othman, Mohd Fairuz Iskandar, Hussian Hassan, Ali Abdul, Talib, Mohammed Saad, Mohammed, Ali Abdul Jabbar

“…K Nearest Neighbor Joins (KNN join) are regarded as highly primitive and expensive operations in the data mining.The efficient use of KNN join has proven good results in finding the objects from two data sets prevailed in the huge databases.This has been achieved with the combination of K-Nearest Neighbor query and join operation to find the distinct objects from different data sets.MapReduce is a newly introduced program with the combination of Map Procedure method and Reduce Method widely used in BigData.MapReduce is enriched with parallel distributed algorithm to find the results on a cluster of data sets in BigData.In this paper,the combination of KNN join and MapReduce methods are utilized on the cluster of data sets in BigData for knowledge discovery.Exploring the pinpoint data from huge data sets stored in Big Data demands the distributed large scale data processing.The present research paper is focusing on generic steps for KNN joins exploration operations on MapReduce.The operations of KNN Join are targeted to perform the data partitioning and data pre-processing and necessary calculations.By utilizing the combination of KNN joins with MapReduce methods on BigData data sets will demonstrate a solution for complex computational analysis. …”
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