Search Results - intelligence based ((((modified algorithm) OR (mining algorithm))) OR (means algorithm))

Improvement anomaly intrusion detection using Fuzzy-ART based on K-means based on SNC Labeling by Zulaiha Ali Othman, Afaf Muftah Adabashi, Suhaila Zainudin, Saadat M. Al Hashmi

“…This paper presents our work to improve the performance of anomaly intrusion detection using Fuzzy-ART based on the K-means algorithm. The K-means is a modified version of the standard K-means by initializing the value K from the value obtained after data mining using Fuzzy-ART and SNC labeling technique. …”
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Enhanced Intelligent Water Drops Algorithm for University Examination Timetabling Problems by Bashar AbedAl Mohdi Talal AlDeeb

“…The IWD is a recent metaheuristic population-based algorithm belonging to the swarm intelligent category which simulates the dynamic of the river systems. …”

A hybrid approach for artificial immune recognition system / Mahmoud Reza Saybani by Mahmoud Reza, Saybani

“…The increasing size of data being stored have created the need for computer-based methods for automatic data analysis. Many researchers, who have developed methods and algorithms within the field of artificial intelligence, machine learning and data mining, have addressed extracting useful information from the data. …”
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Smart agriculture economics and engineering: Unveiling the innovation behind ai-enhanced rice farming by Chuan, Zun Liang, Tham, Ren Sheng, Tan, Chek Cheng, Abraham Lim, Bing Sern, Chong, Yeh Sai

“…This article introduced innovative Artificial Intelligence-based (AI-based) predictive algorithms for short-term rice production, utilizing the Cross Industry Standard Process for Data Mining (CRISP-DM) data science framework. …”
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Computational intelligence based power tracing for nondiscriminatory losses charge allocation and voltage stability improvement. / Zulkifli Abdul Hamid by Abdul Hamid, Zulkifli

“…Subsequently, the developed tracing algorithm was modified in the context of stability index tracing……”
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Sustainable energy management: Artificial intelligence-based electricity consumption prediction in limited dataset environment for industry applications by Chuan, Zun Liang, Tan, Lit Ken, Wee, Angel Chi Chyin, Yim Hin, Tham, Shao, Jie Ong, Jia, Yi Low, Chong, Yeh Sai

“…This study aimed to develop a modified stacked ensemble multivariable Artificial Intelligence (AI)-based predictive algorithm, specifically Stacked Simple Linear Regression and Multiple Linear Regression (SLR-MLR), and Stacked Simple Linear Regression and Multiple Non-Linear Regression (SLR-MNLR) utilizing the Cross Industry Standard Process for Data Mining (CRISP-DM) data science methodology. …”
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Smart Agriculture Economics and Engineering: Unveiling the Innovation Behind AI-Enhanced Rice Farming by Zun Liang, Chuan, Tham, Ren Sheng, Tan, Chek Cheng, Abraham Lim, Bing Sern, David Lau, King Luen, Chong, Yeh Sai

“…To address these challenges, an innovative Artificial Intelligence-based (AI-based) predictive algorithm has been proposed, leveraging the Cross Industry Standard Process for Data Mining (CRISP-DM) data science framework. …”
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Speech enhancement using deep neural network based on mask estimation and harmonic regeneration noise reduction for single channel microphone by Md Jamal, Norezmi

“…Results from TIMIT dataset revealed that average STOI scores for the joint algorithm are higher than those of DNN, conventional HRNR and Log Minimum Mean Square Error (Log-MMSE) algorithms. …”
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Predicting longitudinal dispersion coefficient using ensemble models and optimized multi-layer perceptron models by Gholami M., Ghanbari-Adivi E., Ehteram M., Singh V.P., Najah Ahmed A., Mosavi A., El-Shafie A.

Application Of Neural Network In Malaria Parasites Classification by Lim, Chia Li

“…Hybrid Multilayer Perceptron (HMLP) network with modified recursive prediction error algorithm will be developed using Borland C++ Builder. …”
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Intelligent segmentation of fruit images using an integrated thresholding and adaptive K-means method (TSNKM) by Hambali, Hamirul ’Aini, Syed Abdullah, Sharifah Lailee, Jamil, Nursuriati, Harun, Hazaruddin

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Computational intelligence based power tracing for non discriminatory losses charge allocation and voltage stability improvement / Zulkiffli Abdul Hamid by Abdul Hamid, Zulkiffli

“…Subsequently, the developed tracing algorithm was modified in the context of stability index tracing. …”
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Computational intelligence based power tracing for non discriminatory losses charge allocation and voltage stability improvement / Zulkiffli Abdul Hamid by Abdul Hamid, Zulkiffli

“…Subsequently, the developed tracing algorithm was modified in the context of stability index tracing. …”
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Development of intelligent hybrid learning system using clustering and knowledge-based neural networks for economic forecasting : First phase by Che Mat @ Mohd Shukor, Zamzarina, Md Sap, Mohd Noor

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Artificial neural network approach for electric load forecasting in power distribution company / Hambali M. A ... [et al.] by M. A., Hambali, Y. K, Saheed, M. D, Gbolagade, M, Gaddafi

“…Researchers then performed data preprocessing on the data. Afterwards, data mining algorithms were applied in order to forecast electric load. …”
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Development of a robust intelligent controller for a semi-active car suspension system by Abas, Hesham Ahmed Abdul Mutleba

“…Commonly, the Fuzzy rules are optimized using offline optimization methods such as Differential Evolutionary (DE), Particle Swarms Optimization (PSO), or Artificial Neural Network (ANN) algorithms. In this research, Differential Evolution (DE) algorithm is modified to enhance the Fuzzy logic output gains to increase the performance of PID portion of the Fuzzy-PID controller. …”
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Potential norms detection in social agent societies by Mahmoud M.A., Mustapha A., Ahmad M.S., Ahmad A., Yusoff M.Z.M., Hamid N.H.A.

DATA CLASSIFICATION SYSTEM WITH FUZZY NEURAL BASED APPROACH by LUONG, TRUNG TUAN

“…The project's objective is identifying the available data mining algorithms in data classification and applying new data mining algorithm to perform classification tasks. …”
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An application of predicting student performance using kernel k-means and smooth support vector machine by Sajadin, Sembiring

“…In this study, psychometric factors used as predictor variables, thereare Interest, Study Behavior, Engaged Time, Believe, and Family Support.The rulemodel developed using Kernel K-means Clustering and Smooth Support Vector MachineClassification.Both of these techniquesbased on kernel methodsand relativelynew algorithms of data mining techniques, recently received increasingly popularity in machine learning community. …”
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Investigating the reliability of machine learning algorithms as an advanced tool for ozone concentration prediction by Ayman Mohammed Shaher Yafouz, Mr.

“…The standalone and hybrid models have been tested to evaluate their performance via 5 metrics performances; (Coefficient of Determination (R2), Normalized Root Mean Square Error (NRMSE), Root Mean Square Error (RMSE), Mean Square Error (MSE), Mean Absolute Error (MAE)), and Modified Taylor Diagram. …”