Search Results - (( java implication _ algorithm ) OR ( pattern reduction means algorithm ))

A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition by Babiker, Elsadig Ahmed Mohamed

“…A vector quantization model that incorporate rough sets attribute reduction and rules generation with a modified version of the K-means clustering algorithm was developed, implemented and tested as a part of a speech recognition framework, in which the Learning Vector Quantization (LVQ) neural network model was used in the pattern matching stage. …”
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Optimal short term load forecasting using LSSVM and improved BFOA considering Malaysia pandemic disrupted situation by Zaini, Farah Anishah

“…The LSSVM-IBFOA model demonstrates superior performance compared to standalone LSSVM and LSSVM-BFOA based on Mean Absolute Percentage Error (MAPE), Mean Absolute Error (MAE), Root Mean Squared Error (RMSE), Mean Squared Error (MSE), Normalized RMSE (NRMSE), and Determination Coefficient (R²). …”
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Rule-based filtering algorithm for textual document by Jamil, Nurul Syafidah, Ku-Mahamud, Ku Ruhana, Mohamed Din, Aniza

“…Improper filtration might cause terms that have similar meaning to be removed.Thus, to reduce the high-dimensionality of text, this study proposed a filtering algorithm that is able to filter the important terms from the pre-processed text and applied term weighting scheme to solve synonym problem which will help the selection of relevant term.The proposed filtering algorithm utilizes a keyword library that contained special terms which is developed to ensure that important terms are not eliminated during filtration process.The performance of the proposed filtering algorithm is compared with rough set attribute reduction (RSAR) and information retrieval (IR) approaches.From the experiment, the proposed filtering algorithm has outperformed both RSAR and IR in terms of extracted relevant terms.…”
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Simulation of a smart antenna system by Rosli, Nur Alina Zureen

“…Implementation that revolves around the Least Mean Square (LMS) adaptive algorithm, chosen for its computational simplicity and high stability algorithm into the MATLAB® simulation of an adaptive array of a smart antenna base station system, is to investigate its performance in the presence of multipath components and multiple users. …”
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Optimization Of Pid Controller For Double-Link Flexible Robotic Manipulator Using Metaheuristic Algorithms by Annisa, Jamali, Intan Zaurah, Mat Darus, Hanim, Mohd Yatim, Mat Hussin, Ab Talib

“…Besides, vibration reduction shows great improvement for both link 1 and 2. …”
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Improved undetected error probability model for JTEC and JTEC-SQED coding schemes by Flayyih, Wameedh Nazar, Samsudin, Khairulmizam, Hashim, Shaiful Jahari, Rokhani, Fakhrul Zaman, Ismail, Yehea I.

“…According to the decoding algorithm the errors are classified into patterns and their decoding result is checked for failures. …”
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Adaptive Feature Selection and Image Classification Using Manifold Learning Techniques by ASHRAF, AMNA, MOHD NAWI, NAZRI, MUHAMMAD AAMIR, MUHAMMAD AAMIR

“…Manifold learning techniques aim to the non-linear dimension reduction of data. Dimension reduction is the field of interest and demand of many data analysts and is widely used in computer vision, image processing, pattern recognition, neural networks, and machine learning. …”
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Self learning neuro-fuzzy modeling using hybrid genetic probabilistic approach for engine air/fuel ratio prediction by Al-Himyari, Bayadir Abbas

“…The model was compared to other learning algorithms for NFS such as Fuzzy c-means (FCM) and grid partition algorithm. …”
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Comparative Analysis of Artificial Intelligence Methods for Streamflow Forecasting by YAXING, WEI, HUZAIFA, HASHIM, Lai, Sai Hin, CHONG, KAI LUN, HUANG, YUK FENG, ALI NAJAH, AHMED, MOHSEN, SHERIF, AHMED, EL-SHAFIE

“…For this dataset, wavelet transformation significantly improves the resolution of lag noise when historical streamflow data are used as lagged input variables, producing a 6% reduction in the root-mean-square error. A comparative analysis of convolutional neural networks and artificial neural networks reveals these models’ distinct behavioral patterns. …”
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Pairwise clusters optimization and cluster most significant feature methods for anomaly-based network intrusion detection system (POC2MSF) / Gervais Hatungimana by Hatungimana, Gervais

“…Most of researches in IDS which use k-centroids-based clustering methods like K-means, K-medoids, Fuzzy, Hierarchical and agglomerative algorithms to baseline network traffic suffer from high false positive rate compared to signature-based IDS, simply because the nature of these algorithms risk to force some network traffic into wrong profiles depending on K number of clusters needed. …”
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The implications for ahybrid detection technique against malicious sqlattacks on web applications by Bahjat Arif, Sarajaldeen Akram, Wani, Sharyar

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Optimal planning of photovoltaic distributed generation considering uncertainties using monte carlo pdf embedded MVMO-SH by Norhafidzah, Mohd Saad

“…The probabilistic values of PV generation and load models are employed as the input data to the load flow analysis for the radial distribution network. The load flow patterns will significantly have affected when uncertain PV generation – load models are considered into the power flow algorithm. …”
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Local-based stereo matching algorithm using multi-cost pyramid fusion, hybrid random aggregation and hierarchical cluster-edge refinement by Kadmin, Ahmad Fauzan

“…The estimation of Stereo Matching Algorithm (SMA) is one of the extensive research topics for obtaining the disparity map from two images. …”
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Prediction of Alzheimer disease using improved MMSE ensemble regressor based on magnetic resonance images by Farzan, Ali

“…The same proposed ensemble regression method is used in designing these regressors. Mean square errors range between 0.0064 and 0.0111 and correlation coefficients range between 0.8393 and 0.09355 indicate suitability of proposed algorithm even in predicting other type of features. …”
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Digital Quran With Storage Optimization Through Duplication Handling And Compressed Sparse Matrix Method by Ashraf Saleh Mohammad Alomoush

Analysis and decentralised optimal flow control of heterogeneous computer communication network models by Ku-Mahamud, Ku Ruhana

“…A new method of general model reduction using the Norton' s theorem for general queueing networks in conjunction with the universal maximum entropy algorithm is proposed for the analysis of xix large general closed queueing networks. …”
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Improvement of vertical height accuracy using data fusion technique for terrain mapping in oil palm plantation by Muhadi, Nur 'atirah

“…The weighted value was computed using mean error of the elevation of its relative station, the mean error of the elevation based on classified elevation range and the error pattern based on its relative station. …”
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