Search Results - (( variable predictions clustering algorithm ) OR ( java application optimisation algorithm ))

Prediction of Machine Failure by Using Machine Learning Algorithm by Fakhrurazi, Nur Amalina

“…Model built resulted in variables importance’s ranking and subsequently, prediction can be made. …”
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Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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A machine learning approach of predicting high potential archers by means of physical fitness indicators by Musa, Rabiu Muazu, Anwar, P. P. Abdul Majeed, Zahari, Taha

“…k-nearest neighbour (k-NN) has been shown to be an effective learning algorithm for classification and prediction. However, the application of k-NN for prediction and classification in specific sport is still in its infancy. …”
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A machine learning approach of predicting high potential archers by means of physical fitness indicators by Muazu Musa, Rabiu, Abdul Majeed, Anwar P.P., Taha, Zahari, Chang, Siow Wee, Ab. Nasir, Ahmad Fakhri, Abdullah, Mohamad Razali

“…k-nearest neighbour (k-NN) has been shown to be an effective learning algorithm for classification and prediction. However, the application of k-NN for prediction and classification in specific sport is still in its infancy. …”
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The Identification of High Potential Archers Based on Fitness and Motor Ability Variables: A Support Vector Machine Approach by Zahari, Taha, Rabiu Muazu, Musa, Anwar, P. P. Abdul Majeed, Muhammad Muaz, Alim, Mohamad Razali, Abdullah

“…Hierarchical agglomerative cluster analysis (HACA) was used to cluster the archers based on the performance variables tested. …”
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An evolutionary based features construction methods for data summarization approach by Rayner Alfred, Suraya Alias, Chin, Kim On

“…The DARA algorithm will be applied to summarize data stored in the non-target tables by clustering them into groups, where multiple records stored in non­target tables correspond to a single record i,tored in a target table. …”
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The identification of high potential archers based on relative psychological coping skills variables: a support vector machine approach by Taha, Z., Musa, R.M., Majeed, A.P.P.A, Abdullah, M.R., Zakaria, M.A., Alim, M.M., Jizat, J.A.M., Ibrahim, M.F.

“…Support Vector Machine (SVM) has been revealed to be a powerful learning algorithm for classification and prediction. However, the use of SVM for prediction and classification in sport is at its inception. …”
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An application of predicting student performance using kernel k-means and smooth support vector machine by Sajadin, Sembiring

“…Eachmember of the clusters labeledwith their performance index to describe the current condition of student performance.The prediction accuracy of predicting modelproposed have thelowest accuracy 61%(R2= 0.61)in predicting Good performance indexand thehighest accuracy 93.67% (R2= 0.9367)in predicting Poor Performance index. …”
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The identification of high potential archers based on relative psychological coping skills variables: A Support Vector Machine approach by Zahari, Taha, Rabiu Muazu, Musa, Anwar, P. P. Abdul Majeed, Mohamad Razali, Abdullah, Muhammad Aizzat, Zakaria, Muhammad Muaz, Alim, Jessnor Arif, Mat Jizat, Mohamad Fauzi, Ibrahim

“…Support Vector Machine (SVM) has been revealed to be a powerful learning algorithm for classification and prediction. However, the use of SVM for prediction and classification in sport is at its inception. …”
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Adaptive neuro-fuzzy model with fuzzy clustering for nonlinear prediction and control by Al-Himyari, Bayadir Abbas, Yasin, Azman, Gitano, Horizon

“…Nonlinear systems have more complex manner and profoundness than linear systems.Thus, their analyses are much more difficult.This paper presents the use of neuro-fuzzy networks as means of implementing algorithms suitable for nonlinear black-box prediction and control.In engineering applications, two attractive tools have emerged recently.These two attractive tools are: the artificial neural networks and the fuzzy logic system. …”
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Parameter estimation and outlier detection for some types of circular model / Siti Zanariah binti Satari by Satari, Siti Zanariah

“…Here, we introduce a measure of similarity based on the circular distance and obtain a cluster tree using the single linkage clustering algorithm. …”
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Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed by Borujeni, Sattar Chavoshi

“…In conventional hard clustering approach, the number of clusters was determined by hierarchical clustering and two-step cluster analysis; then the sites were allocated to the appropriate cluster by k-means clustering method. …”
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Depression prediction system from Twitter’s tweet by using sentiment analysis / Nur Amalina Kamaruddin by Kamaruddin, Nur Amalina

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An improved machine learning model of massive Floating Car Data (FCD) based on Fuzzy-MDL and LSTM-C for traffic speed estimation and prediction by Ahanin, Fatemeh

“…The existing research in traffic speed prediction used LSTM with single variable (traffic speed) and multi variables (traffic speed and vehicle headway). …”
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Response surface analysis, clustering, and random forest regression of pressure in suddenly expanded high-speed aerodynamic flows by Afzal, Asif, Aabid, Abdul, Khan, Ambareen, Khan, Sher Afghan, Rajak, Upendra, Verma, Tikendra Nath, Kumar, Rahul

“…The K-means algorithm performs a clustering analysis of this enormous data, which provides useful information and patterns. …”
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An ensemble of neural network and modified grey wolf optimizer for stock prediction by Das, Debashish

“…The research implements stock prediction analysis as a case study for training the neural network by adopting MGWO algorithm. …”
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Predicting 30-day mortality after an acute coronary syndrome (ACS) using machine learning methods for feature selection, classification and visualization by Nanyonga Aziida, Sorayya Malek, Firdaus Aziz, Khairul Shafiq Ibrahim, Sazzli Kasim

“…Feature selection methods such as Boruta, Random Forest (RF), Elastic Net (EN), Recursive Feature Elimination (RFE), learning vector quantization (LVQ), Genetic Algorithm (GA), Cluster Dendrogram (CD), Support Vector Machine (SVM) and Logistic Regression (LR) were combined with RF, SVM, LR, and EN classifiers for 30-day mortality prediction. …”
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Data Analysis and Rating Prediction on Google Play Store Using Data-Mining Techniques by Kayalvily, Tabianan, Denis, Arputharaj, Mohd Norshahriel, Abd Rani, Sarasvathi, Nahalingham

“…The goal of using a Decision Tree is to create a training model that can use to predict the class or value of the target variable by learning simple decision rules inferred from prior data. …”
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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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Landslide susceptibility mapping using decision-tree based chi-squared automatic interaction detection (CHAID) and logistic regression (LR) integration by Althuwaynee, Omar F., Pradhan, Biswajeet, Ahmad, Noordin

“…LR model was used to find the corresponding coefficients of best fitting function that assess the optimal terminal nodes. A cluster pattern of landslide locations was extracted in previous study using nearest neighbor index (NNI), which were then used to identify the clustered landslide locations range. …”
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