Search Results - (( variable step learning algorithm ) OR ( java applications 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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SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA by AHMED IZZELDIN, HUZAIFA TAWFEIG

“…This thesis gives a systematic investigation of various MLP learning mainly Sliding Window (SW) learning mode which is treated as the adaptation of offline algorithms into online application Consequently this thesis reviews various offline algorithms including: batch backpropagation, nonlinear conjugate gradient, limited memory and full-memory Broyden, Fletcher, Goldfarb and Shanno algorithms and different forms of the latest proposed bimary ensemble learning. …”
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Variable step size least mean square optimization for motion artifact reduction: A review by Zailan, K.A.M., Hasan, M.H., Witjaksono, G.

“…Therefore, we propose a research to formulate an improved motion artifact reduction approach using variable step-size least mean square (VSSLMS). The objective of this paper is to review VSSLMS for motion artifact reduction. …”
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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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Linking Bayesian Network and Intensive Care Units Data: A Glycemic Control Study by Abu-Samah A., Abdul Razak N.N., Mohamad Suhaimi F., Jamaludin U.K., Chase G.

Towards personalized intensive care decision support using a Bayesian network: A multicenter glycemic control study by Abu-Samah A., Razak N.N.A., Suhaimi F.M., Jamaludin U.K., Chase J.G.

The Crop Price Prediction Using Machine Learning: Preliminary Stage by Ramya, T.K., Shreedhara N, Hegde, Mohd Norshahriel, Abd Rani

“…The back-end predictive model for this project is created utilizing machine learning algorithms. The steps involved in creating a predictive model are data collecting, data cleaning, data mining, and validation. …”
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Tangible interaction learning model to enhance learning activity processes among children with dyslexia by Jamalai@Jamali, Siti Nurliana

“…To find optimum variables, Machine Learning approach needs to be utilized. …”
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Detection of Denial of Service Attacks against Domain Name System Using Neural Networks by Rastegari, Samaneh

“…In the current research for our machine learning engine, we aimed to find the optimum machine learning algorithm to be used as an IDS. …”
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Modeling flood occurences using soft computing technique in southern strip of Caspian Sea Watershed by Borujeni, Sattar Chavoshi

“…Among the available learning algorithms in the Neural Network Toolbox of MATLAB, three algorithms, gradient descent back propagation (TRAINGD), gradient descent with adaptive learning rule back propagation (TRAINGDA) and the Levenberg-Marquardt (TRAINLM) were studied. …”
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Critical Appraisement of Slope Failure Contributing Parameters for Slope Risk Assessment System of Western Sarawak via Multi Statistical Approaches with Artificial Neural Networ... by Nur Hisyam, Ramli

“…The Landslide Susceptibility Model yielded a Root Mean Squared Error of 0.0057 with the hyperparameter of the model being eight neurons in a single hidden layer, a backpropagation learning algorithm, a learning rate of 0.001, and a maximum step of 1E+8. …”
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Automated detection and evaluation of ischemic stroke on ct brain imaging using machine learning techniques by Sharuddin, Nur Amirah Atikah

“…This study investigates the application of machine learning algorithms for the detection of ischemic stroke using CT brain images. …”
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Analysis using data mining techniques: the exploration and review data of diabetes patients / Syarifah Adilah Mohamed Yusoff ... [et al.] by Mohamed Yusoff, Syarifah Adilah, Othman, Jamal, Johan, Elly Johana, Mohd Mydin, Azlina, Wan Mohamad, Wan Anisha

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Genetic-based approach for cue phrase selection in dialogue act recognition by Yahya, Anwar Ali, Ramli, Abdul Rahman

“…Automatic cue phrase selection is a crucial step for designing a dialogue act recognition model using machine learning techniques. …”
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Enhancing understanding of programming concepts through physical games by Raja Yusof, Raja Jamilah, Habib, Ahsan

“…We regularly discussed and improved on how the steps of the games should be executed especially regarding the sorting algorithm. …”
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Intelligent imputation method for mix data-type missing values to improve data quality by Alabadla, Mustafa R. A.

“…To find optimum variables, Machine Learning approach needs to be utilized. …”
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Evaluation and Comparative Analysis of Feature Extraction Methods on Image Data to increase the Accuracy of Classification Algorithms by Rachmad, Iqbal, Tri Basuki, Kurniawan, Misinem, ., Edi Surya, Negara, Tata, Sutabri

“…The feature extraction methods evaluated were Grayscale Pixel Values, Mean Pixel Value of Channels, and Extracting Edge Features. The classification algorithm used in this research is the Convolutional Neural Network (CNN) algorithm. …”
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Evaluation of machine learning classifiers in faulty die prediction to maximize cost scrapping avoidance and assembly test capacity savings in semiconductor integrated circuit (IC)... by Mohd Fazil, Azlan Faizal, Mohd Shaharanee, Izwan Nizal, Mohd Jamil, Jastini

“…The other group, will use auto machine learning (ML) to run multiple classifiers automatically and only top 3 to be selected for next step. …”
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Predictive Framework for Imbalance Dataset by Megat Norulazmi, Megat Mohamed Noor

“…The major contribution of this research is a step by step guideline which consists of methods/approaches in generating a prediction for process materials.…”
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Physiological signals as predictors of mental workload: Evaluating single classifier and ensemble learning models by Nailul, Izzah, Sutarto, Auditya Purwandini, Hendi, Ade, Ainiyah, Maslakhatul, Muhammad Nubli, Abdul Wahab

“…This study aims to develop machine learning (ML) models for predicting mental workload using Heart Rate Variability (HRV) as a representation of the Autonomic Nervous System (ANS) physiological signals. …”
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