Search Results - (( program using backpropagation algorithm ) OR ( java application optimisation algorithm ))

Backpropagation algorithm for classification problem: academic performance prediction model for UiTM Melaka Mengubah Destini Anak Bangsa (MDAB) program. / Fadhlina Izzah Saman, Nur... by Saman, Fadhlina Izzah, Zainuddin, Nurulhuda, Md Shahid, Khairiyah

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Recognition of isolated elements picture using backpropagation neural network / Melati Sabtu by Sabtu, Melati

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Particle swarm optimization for neural network learning enhancement by Abdull Hamed, Haza Nuzly

“…Backpropagation (BP) algorithm is widely used to solve many real world problems by using the concept of Multilayer Perceptron (MLP). …”
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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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Comparative Analysis Using Bayesian Approach To Neural Network Of Translational Initiation Sites In Alternative Polymorphic Contex by Herman, Nanna Suryana, Husin, Nurul Arneida, Hussin, Burairah

“…The objectives of this paper are to develop useful algorithms and to build a new classification model for the case study.The first approach of neural network includes training on algorithms of Resilient Backpropagation,Scaled Conjugate Gradient Backpropagation and Levenberg-Marquardt.The outputs are used in comparison with Bayesian Neural Network for efficiency comparison.The results showed that Resilient Backpropagation have the consistency in all measurement but performs less in accuracy.In second approach,the Bayesian Classifier_01 outperforms the Resilient Backpropagation by successfully increasing the overall prediction accuracy by 16.0%.The Bayesian Classifier_02 is built to improve the accuracy by adding new features of chemical properties as selected by the Information Gain Ratio method,and increasing the length of the window sequence to 201.The result shows that the built model successfully increases the accuracy by 96.0%.In comparison,the Bayesian model outperforms Tikole and Sankararamakrishnan (2008) by increasing the sensitivity by 10% and specificity by 26%. …”
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Applications of IoT and Artificial Intelligence in Water Quality Monitoring and Prediction: A Review by Mustafa H.M., Mustapha A., Hayder G., Salisu A.

Development of thumbprint recognition system using Matlab / Wan Hasnizam Wan Hassan by Wan Hassan, Wan Hasnizam

“…The algorithm used in order to achieve the result is called feedforward backpropagation neural network.…”
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Determining Suitable Program For SPM Holder Using Neural Network Approach by Noraisah, Sudin

“…The basic architecture are multilayer feedforward networks, trained using the Backpropagation algorithm. The evaluation using 302 data sets showed that the developed architecture is very useful for high dimensional input vectors. …”
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Artificial neural network (ANN) modeling & validation to predict compression index of tropical soft soil by Yong, Shirley Xiao Wei

“…Therefore, a programming was written by using MATLAB 6.5 and train with eight different training algorithm, namely Resilient Backpropagation (rp), Conjugate Gradient Polak-Ribiére algorithm (cgp), Scale Conjugate Gradient (scg), Levenberg-Marquardt algorithm (lm), BFGS Quasi-Newton (bfg), Conjugate Gradient with Powell/Beale Restarts (cgb), Fletcher-Powell Conjugate Gradient (cgf), and One-step Secant (oss) have been compared for the best prediction of Cc. …”
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Parallel simulation of character recognition problems using NEUCOMP2 by Evans, David J., Sulaiman, Md. Nasir

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Face classification for three major ethnic of Orang Asli using Back Propagation Neural Network / Nor Intan Shafini Nasaruddin by Nasaruddin, Nor Intan Shafini

“…Image preprocessing and image extraction are done by using MATLAB. The image classification prototype is developed by using JAVA programming language which is based on supervised learning algorithm, Backpropagation Neural Network. …”
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Automatic database of robust neural network forecasting / Saadi Ahmad Kamaruddin, Nor Azura Md. Ghani and Norazan Mohamed Ramli by Ahmad Kamaruddin, Saadi, Md. Ghani, Nor Azura, Mohamed Ramli, Norazan

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Optimization of Multilayer Perceptron (MLP) network training algorithms for agrwood oil quality separation / Noratikah Zawani Mahabob ... [et al.] by Mahabob, Noratikah Zawani, Mohd Yusoff, Zakiah, Ismail, Nurlaila, Taib, Mohd Nasir

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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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Detection of arcing fault in underground distribution cable using artificial neural network by Chan, Wei Kian

“…A Multi-layer Perceptron (MLP) with Backpropagation (BP) learning is used to discriminate arcing faults from normal load condition. …”
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Nuclear Power Plant Burst Parameters Prediction During a Loss-of-Coolant Accident Using an Artificial Neural Network by Tumpa, P.P., Saiful Islam, M., May, Z., Khorshed Alam, M.

“…In this research, a feedforward backpropagation algorithm with the logsig activation function is used to build this neural network model. …”
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