Search Results - (( module active learning algorithm ) OR ( java implementation mining algorithm ))

Direct approach for mining association rules from structured XML data by Abazeed, Ashraf Riad

“…The thesis also provides a two different implementation of the modified FLEX algorithm using a java based parsers and XQuery implementation. …”
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Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…Using the J48 tree algorithm implemented through WEKA API on a Java Servlet, data provided is processed to derive a health index of the plant, with the possible outcomes set to “Good,” “Okay”, or “Bad”. …”
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Scalable approach for mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

“…Many techniques have been proposed to tackle the problem of mining XML data we study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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Mining association rules from structured XML data by Abazeed, Ashraf Riad, Mamat, Ali, Sulaiman, Md. Nasir, Ibrahim, Hamidah

“…Many techniques have been proposed to tackle the problem of mining XML data. We study the various techniques to mine XML data and yet We presented a java based implementation of FLEX algorithm for mining XML data.…”
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A web-based implementation of k-means algorithms by Lee, Quan

“…This stinginess of proximity measures in data mining tools is stifling the performance of the algorithm. …”
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Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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Computational Thinking (Algorithms) Through Unplugged Programming Activities: Exploring Upper Primary Students’ Learning Experiences by Bih Loong, Lim, Chwen Jen, Chen

“…A total of 31 students from a rural primary school were exposed to the learning about the algorithm concept (an aspect of CT skills) via UPA learning materials. …”
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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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Pair-associate learning with modulated spike-time dependent plasticity by Yusoff, Nooraini, Grüning, André, Notley, Scott

“…We propose an associative learning model using reward modulated spike-time dependent plasticity in reinforcement learning paradigm. …”
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Spatio-temporal event association using reward-modulated spike-time-dependent plasticity by Yusoff, Nooraini, Ibrahim, Mohammed Fadhil

“…The results demonstrate that the algorithm can also learn temporal sequence detection.Learning has also been tested in face-voice association using real biometric data.The loose dependency between the model's anatomical properties and functionalities could offer a wide range of applications, especially in complex learning environments.…”
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Investigation of An Early Prediction System of Cardiac Arrest Using Machine Learning Techniques by Muhammad Afnan, Mohammad Nasir

“…An effective machine learning approach created from a separate examination of many machine learning algorithms in WEKA should be applied for the correct identification of heart disease. …”
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Stimulus-stimulus association via reinforcement learning in spiking neural network by Yusoff, Nooraini, Kabir Ahmad, Farzana

“…In this paper, we propose an algorithm that performs stimulus-stimulus association via reinforcement learning.In particular, we develop a recurrent network with dynamic properties of Izhikevich spiking neuron model and train the network to associate a stimulus pair using reward modulated spike-time dependent plasticity.The learning algorithm associates a prime stimulus, known as the predictor, with a second stimulus, known as the choice, comes after an inter-stimulus interval.The influence of the prime stimulus on the neural response after the onset of the later stimulus is then observed.A series of probe trials resemble the retrospective and prospective activities in human response processing…”
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An ELM-based single input rule module and its application in power generation by Yaw C.T., Wong S.Y., Yap K.S.

“…Extreme Learning Machine (ELM) is widely known as an effective learning algorithm than the conventional learning methods from the point of learning speed as well as generalization. …”

Unified neural network controller of series active power filter for power quality problems mitigation by Ghazanfarpour, Behzad

“…First, Widrow-Hoff algorithm is examined and its constant learning rate is modified by adding an adaptive learning rule to change the learning rate value. …”
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A resource-aware content adaptation approach for e-learning environment / Mohd Faisal Ibrahim by Ibrahim, Mohd Faisal

“…It consists of a device database and two processing components: (1) device identification module and (2) device capabilities detection module. …”
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Towards Autonomous Farming -A Novel Scheme based on Learning to Prediction and Optimization for Smart Greenhouse Environment Control by Ullah, I., Fayaz, M., Aman, M., Kim, D.

“…Comparative analysis of the results shows that the proposed model maintains the desired indoor environment for maximizing plant production with reduced energy consumption i.e., it achieves 61.97 reduced energy consumption than baseline scheme, 11.73 better than optimization scheme without learning modules. Furthermore, proposed model achieves 67.96 and 12.56 reduction in cost when compared to the baseline scheme and optimization scheme without learning modules, respectively. …”
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Towards Autonomous Farming -A Novel Scheme based on Learning to Prediction and Optimization for Smart Greenhouse Environment Control by Ullah, I., Fayaz, M., Aman, M., Kim, D.

“…Comparative analysis of the results shows that the proposed model maintains the desired indoor environment for maximizing plant production with reduced energy consumption i.e., it achieves 61.97 reduced energy consumption than baseline scheme, 11.73 better than optimization scheme without learning modules. Furthermore, proposed model achieves 67.96 and 12.56 reduction in cost when compared to the baseline scheme and optimization scheme without learning modules, respectively. …”
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Toward Autonomous Farming - A Novel Scheme Based on Learning to Prediction and Optimization for Smart Greenhouse Environment Control by Ullah, I., Fayaz, M., Aman, M., Kim, D.

“…Comparative analysis of the results shows that the proposed model maintains the desired indoor environment for maximizing plant production with reduced energy consumption, i.e., it achieves 61.97 reduced energy consumption than the baseline scheme, 11.73 better than the optimization scheme without learning modules. Furthermore, the proposed model achieves 67.96 and 12.56 reduction in cost when compared to the baseline scheme and optimization scheme without learning modules, respectively. …”
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Revolutionizing Perimeter Intrusion Detection: A Machine Learning-Driven Approach with Curated Dataset Generation for Enhanced Security by Pitafi, S., Anwar, T., Dewa Made Widia, I., Yimwadsana, B.

“…After collecting the data from above mentioned sensors we applied machine learning algorithms DBSCAN to cluster the data points and K-NN classification to classify those clusters in one-dimensional data, but the results were not much satisfying. …”
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Output prediction of grid-connected photovoltaic system using artificial neural network / Nurul Khairaini Nor Adzman by Nor Adzman, Nurul Khairaini

“…The performance of ANN model was tested using different algorithm and activation function. The number of neuron has been varied from 1-20 while the momentum rate and the learning rate varies from 0.05 until 1. …”
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