Search Results - (( java application sensor algorithm ) OR ( problem implementation svm algorithm ))

Gender identification using support vector machines by Nur Ayuni Binti Jalaluddin

“…This thesis is introduces SVM theory application and its algorithmic implementations.…”

Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Hybridize Particle Swarm Optimization (PSO) as a searching algorithm and support vector machine (SVM) as a classifier had been implemented to cope with this problem. …”
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Thematic textual hadith classification: an experiment in rapidminer using support vector machine (SVM) and naïve bayes algorithm by Yusof, Norzihani, Rosidi, Siti Aishah Rosidi, Ibrahim, Nuzulha Khilwani Ibrahim, Ahmed Ali, Ahmed El-Mogtaba Bannga

“…From the results, the different value of accuracy for both SVM and Naïve Bayes Algorithm was 2.4%. The Naïve Bayes Algorithm displayed better result comparing to SVM. …”
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Optimizing in-car-abandoned children’s sounds detection using deep learning algorithms / Nur Atiqah Izzati Md Fisol by Md Fisol, Nur Atiqah Izzati

“…Children abandoned in vehicles is a critical issue that has led to numerous fatal injuries worldwide. To address this problem, an optimized in-car-abandoned children's sounds detection model using deep learning algorithms is proposed. …”
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An Arabic hadith text classification model using convolutional neural network and support vector machine / Mohd Irwan Mazlin by Mazlin, Mohd Irwan

“…Second, parameter tuning is conducted to find the best parameter for CNN-SVM. Third, the model (CNN-SVM, CNN and SVM) is monitored to see if their performance predicts unseen data. …”
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Autism Spectrum Disorder Classification Using Deep Learning by Abdulrazak Yahya, Saleh, Lim Huey, Chern

“…The CNN algorithm produces better results with an accuracy of 97.07%, compared with the SVM algorithm. …”
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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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Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…The process begins through the monitoring of plants using sensors connected to the Arduino device. Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. …”
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Talent classification using support vector machine technique / Hamidah Jantan, Norazmah Mat Yusof and Mohd Hanapi Abdul Latif by Jantan, Hamidah, Mat Yusof, Norazmah, Abdul Latif, Mohd Hanapi

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Design Of Robot Motion Planning Algorithm For Wall Following Robot by Ali Hassan, Muhamad Khairul

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Classification of transient disturbance using Wavelet based support vector machine / Fahteem Hamamy Anuwar by Anuwar, Fahteem Hamamy

“…In this research, Multilayer perception (MLP) of feedforward Artificial Neural Network (ANN) has also been used as the classifier and comparison are made between the SVM and ANN method. The SVM results show that RBF kernel is superior to linear kernel in classifying the transient with average percentage of 83% This research has also proved that SVM has higher performance than the backpropagation algorithm of the ANN.…”
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Author identification for under-resourced language Kadazandusun by Nursyahirah, Tarmizi, Suhaila, Saee, Dayang Hanani, Abang Ibrahim

“…The workflow of Author Identification implements the machine learning approach to solve the single-labelled multi-class problem and predict the author of a given message in KadazanDusun. …”
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Hospital site suitability assessment using three machine learning approaches: evidence from the Gaza strip in Palestine by Almansi, Khaled Yousef, Mohamed Shariff, Abdul Rashid, Abdullah, Ahmad Fikri, Syed Ismail, Sharifah Norkhadijah

“…The CFS analysis shows very high correlations with R2 values of 0.94, 0. 93, and 0.75 for the SVM, MLP, and LR models, respectively. Moreover, based on areas under the ROC curve, the MLP model produced a prediction accuracy of 84.90%, SVM of 75.60%, and LR of 64.40%. …”
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Human activity recognition via accelerometer and gyro sensors by Tee, Jia Lin

“…To implement the data engineering system proposed, two mobile applications, SensorData and SensorDataLogger with user-friendly interfaces and intuitive functionalities are developed using Java programming language and Android Studio. …”
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AMOR: an adaptive, multimodal architecture for visual object recognition by James Mountstephens

“…The specific objectives of this research were to design, implement and evaluate the proposed architecture. The architecture design was formalised mathematically and algorithmically in the form of "reclassification", implemented in custom Matlab code and evaluated by comparison to existing visual-only methods for object recognition. …”
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Hybrid feature selection of microarray prostate cancer diagnostic system by Mohd Ali, Nursabillilah, Hanafi, Ainain Nur, Karis, Mohd Safirin, Shamsudin, Nur Hazahsha, Shair, Ezreen Farina, Abdul Aziz, Nor Hidayati

“…This work proposes a new hybrid feature selection method, namely the relief-F (RF)-genetic algorithm (GA) with support vector machine (SVM) classification method. …”
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SYN Flood detection via machine learning / Muhammad Muhaimin Aiman Mazlan by Mazlan, Muhammad Muhaimin Aiman

“…The core detection and prevention algorithm which is the support vector machine (SVM) were implemented in this project. …”
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Semi-supervised learning for feature selection and classification of data / Ganesh Krishnasamy by Ganesh , Krishnasamy

“…Furthermore, HSS-ELM maintains almost all the advantages of the traditional ELM such as the significant training efficiency and straightforward implementation for multiclass classification problems. …”
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Using convolution neural networks for improving customer requirements classification performance of autonomous vehicle by Hao, Wang, Asrul, Adam, Fengrong, Han

“…Most of conventional algorithms, such as, Naive Bayes, MAXENT, and support vector machine (SVM), only use limited human engineered features and their accuracy for customized corpus in sentences classification are proven low which is less than 50 percent. …”
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Fraud detection in shipping industry based on location using machine learning comparison techniques by Ganesan Subramaniam, Mr.

“…A number of popular existing algorithms were used to execute the model developed in Rapid tool such as Naïve Bayes , Neural Net , Deep Learning, Decision Tree, Logistic Regression, SVM and k-NN. …”