Search Results - parallel information selection algorithm
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Automated plant recognition system based on multi-objective parallel genetic algorithm and neural network
Published 2014“…First, the best set of structures for feed forward neural network were found by multi objective parallel genetic algorithm. This approach regarded three criteria involving mean square error, Akaike information criterion and minimum description length to rate different feed forward neural network structures and to select the best set of them. …”
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Image classification using two dimensional wavelet coefficients with parallel computing
Published 2020“…User is authorized to select and name any specified region from the image, and store the colour, brightness, size, and various kind of information together with the selected area as the individual characteristics for the particular region. …”
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A scheduling algorithm for WDM optical networks
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Projecting named entity tags from a resource rich language to a resource poor language
Published 2012“…Named Entities (NE) are the prominent entities appearing in textual documents.Automatic classification of NE in a textual corpus is a vital process in Information Extraction and Information Retrieval research. …”
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Projecting named entity tags from a resource rich language to a resource poor language
Published 2013“…Automatic classification of NE in a textual corpus is a vital process in Information Extraction and Information Retrieval research. …”
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Projecting named entity tags from a resource rich language to a resource poor language
Published 2013“…Automatic classification of NE in a textual corpus is a vital process in Information Extraction and Information Retrieval research. …”
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Projecting named entity tags from a resource rich language to a resource poor language
Published 2013“…Automatic classification of NE in a textual corpus is a vital process in Information Extraction and Information Retrieval research. …”
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An evolutionary-based term reduction approach to bilingual clustering of Malay-English corpora
Published 2017“…The objective in this study is to study the effects of reducing terms considered in clustering bilingual corpus in parallel for English and Malay documents. In this study, a genetic algorithm (GA) is used in order to reduce the number of feature selected. …”
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Conference or Workshop Item -
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Hybrid ANN and Artificial Cooperative Search Algorithm to Forecast Short-Term Electricity Price in De-Regulated Electricity Market
Published 2019“…Therefore, this research proposes a hybrid method for electricity price forecasting via artificial neural network (ANN) and artificial cooperative search algorithm (ACS). In parallel, a feature selection technique based on the combination of mutual information (MI) and neural network (NN) is developed in this study to select the input variables subsets, which have substantial impact on forecasting of electricity price. …”
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Hybrid harmony search-artificial intelligence models in credit scoring
Published 2019“…Then, the two types of features importance computed from RF algorithm are utilized for the attributes explanation. …”
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Thesis -
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Extreme air pollutant data analysis using classical and Bayesian approaches
Published 2015“…MTM algorithm is an extension of MH algorithm, designed to improve the convergence of MH algorithm by performing parallel computation. …”
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Web based personalized university timetable for UiTM students using genetic algorithm / Mohd Radhi Fauzan Jamli and Ahmad Firdaus Ahmad Fadzil
Published 2024“…Future work entails enhancing system robustness through comprehensive contingency planning, real-time data integration, and algorithmic optimization, with a focus on refining the genetic algorithm and exploring parallel processing techniques to further enhance efficiency and scalability.…”
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Prognosis of early cervical carcinoma using gene expression profiling
Published 2015“…Additionally, stochastic proximity embedding (SPE) was applied to reducing the number of attributes by selecting the most informative genes of the input dataset. …”
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Proceeding Paper -
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining.
Published 2005“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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On line fault detection for transmission line using power system stabilizer signals
Published 2007“…Hence, this study will show that not only the PSS able to compensate the damping due to the disturbance but also by using the developed algorithm it succeeds to detect and classify the fault conditions on the parallel transmission lines.…”
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Unified GPU Technique to Boost Confidentiality, Integrity and Trim Data Loss in Big Data Transmission
Published 2020“…Confidentiality and integrity are further enhanced by integrating advanced audio steganography that uses a distinctive sample selection for hiding bits. Additionally, the implementation of the proposed innovative integrated technique in the graphics processing unit (GPU) environment increases the execution speed and reduces time complexity with extended parallel processing power. …”
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