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

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

Get full text
Get full text

Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

Get full text
Get full text

Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…Attached sensors generate data and send these data to the Java Servlet application through a WIFI module. These data are processed and stored in appropriate formats in a MySQL server database. …”
Get full text
Get full text
Get full text

Mining Sequential Patterns Using I-PrefixSpan by Dhany , Saputra, Rambli Dayang, R.A., Foong, Oi Mean

“…Sequential pattern mining is a relatively new data-mining problem with many areas of application. …”
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text

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. …”
Get full text
Get full text
Get full text
Get full text

Mining Sequential Patterns using I-PrefixSpan by Saputra , Dhany, Dayang R.A. Rambli, Foong, Oi Mean

Get full text
Get full text

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. …”
Get full text
Get full text

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.…”
Get full text
Get full text

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

“…The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. The proposed model will be tested and evaluated on both NSL-KDD and KDD-CUP 99 using several performance metrics.…”
Get full text
Get full text

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. …”
Get full text
Get full text

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…”
Get full text
Get full text
Get full text

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. …”
Get full text
Get full text

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. …”
Get full text
Get full text

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. …”
Get full text
Get full text

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. …”
Get full text
Get full text

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. …”
Get full text
Get full text

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. …”
Get full text
Get full text

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. …”
Get full text
Get full text