Search Results - (( towards implementation svm algorithm ) OR ( java application optimisation algorithm ))

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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Adoption of machine learning algorithm for analysing supporters and non supporters feedback on political posts / Ogunfolajin Maruff Tunde by Ogunfolajin Maruff , Tunde

“…The support vector machines (SVM) algorithm obtained the overall best results of 94.5% accuracy, 91.8% precision, 91.7% recall, and 91.1% f-Measure while the naïve bayes (NB) algorithm obtained the best AUC score of 0.944 with the tweet data of Dato Seri Anwar. …”
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Predicting Suicidal Ideation Via Social Media by Boon, Kar Lih

“…Three Machine Learning algorithms are implemented to predict the result and outcome which are Support Vector Machine (SVM), Decision Tree and Naive Bayes (NB). …”
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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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Design of Predictive Model for TCM Tongue Diagnosis In Malaysia Using Machine Learning by Koe, Jia Chi

“…Six supervised machine learning algorithms (Linear Regression, Logistic Regression, K Nearest Neighbors (KNN), Decision Trees (DT), Support Vector Machine (SVM) and Random Forest) are used to perform disease prediction. …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

“…The proposed algorithm is compared with the state-of-the-art feature selection algorithms using three different datasets. …”
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Productivity monitoring in building construction projects: a systematic review by Alaloul, W.S., Alzubi, K.M., Malkawi, A.B., Al Salaheen, M., Musarat, M.A.

“…Although previous studies have been implemented toward reducing these limitations, a gap still exists in the automated monitoring of construction productivity. …”
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Productivity monitoring in building construction projects: a systematic review by Alaloul, W.S., Alzubi, K.M., Malkawi, A.B., Al Salaheen, M., Musarat, M.A.

“…Although previous studies have been implemented toward reducing these limitations, a gap still exists in the automated monitoring of construction productivity. …”
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Productivity monitoring in building construction projects: a systematic review by Alaloul, W.S., Alzubi, K.M., Malkawi, A.B., Al Salaheen, M., Musarat, M.A.

“…Although previous studies have been implemented toward reducing these limitations, a gap still exists in the automated monitoring of construction productivity. …”
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Productivity monitoring in building construction projects: a systematic review by Alaloul, W.S., Alzubi, K.M., Malkawi, A.B., Al Salaheen, M., Musarat, M.A.

“…Although previous studies have been implemented toward reducing these limitations, a gap still exists in the automated monitoring of construction productivity. …”
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Productivity monitoring in building construction projects: a systematic review by Alaloul, W.S., Alzubi, K.M., Malkawi, A.B., Al Salaheen, M., Musarat, M.A.

“…Although previous studies have been implemented toward reducing these limitations, a gap still exists in the automated monitoring of construction productivity. …”
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Ganoderma boninense classification based on near-infrared spectral data using machine learning techniques by Mas Ira Syafila, Mohd Hilmi Tan, Mohd Faizal, Jamlos, Ahmad Fairuz, Omar, Kamarulzaman, Kamarudin, Mohd Aminudin, Jamlos

“…Four different ML algorithms are tested for prediction of G. boninense infection: K-Nearest Neighbour (kNN), Naïve Bayes (NB), Support Vector Machine (SVM) and Decision Tree (DT) are tested which depicted DT algorithm achieves a satisfactory overall performance with high accuracy up to 93.1% and F1-score of 92.6% compared to other algorithms. …”
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Reduced torque ripple and switching frequency using optimal DTC switching strategy for open-end winding induction machines by Abd Rahim, Muhd Khairi

“…The main benefit of the proposed strategy is its simplicity, where the DTC improvements can be obtained without the common approach, i.e. the use of Space Vector Modulation (SVM) which involves complex control algorithms. …”
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