Search Results - (( learned generated using algorithm ) OR ( java application 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. …”
Get full text
Get full text
Get full text

Automated bilateral negotiation with incomplete information in the e-marketplace. by Jazayeriy, Hamid

“…The reason is that, SRT algorithm is sensitive to the accuracy of the learned preferences while MGT algorithm can generate Pareto-optimal offers even with an approximation of the learned preferences.…”
Get full text
Get full text

Pairwise Test Suite Generation Using Adaptive Teaching Learning-Based Optimization Algorithm with Remedial Operator by Fakhrud, Din, Kamal Z., Zamli

“…Being a NP-complete problem, pairwise test suite generation problem has been addressed using several meta-heuristic algorithms including the Fuzzy Adaptive Teaching Learning-based Optimization (ATLBO) algorithm in the literature. …”
Get full text
Get full text
Get full text

Prediction of hydropower generation via machine learning algorithms at three Gorges Dam, China by Sattar Hanoon M., Najah Ahmed A., Razzaq A., Oudah A.Y., Alkhayyat A., Feng Huang Y., kumar P., El-Shafie A.

“…Three different scenarios are examined, such as scenario1 (SC1): used to predict daily power generation, scenario 2 (SC2): used to predict power generation for monthly prediction and scenario 3 (SC3): used to predict hydropower generation (HPG) seasonally. …”

Clustering ensemble learning method based on incremental genetic algorithms by Ghaemi, Reza

“…Moreover, experiments demonstrate that final clustering solution generated by the proposed incremental genetic-based clustering ensemble algorithm using the pattern ensemble learning method possess comparative or better clustering accuracy than clustering solutions generated by the incremental genetic-based clustering ensemble algorithms using other recombination operators. …”
Get full text
Get full text

New Learning Models for Generating Classification Rules Based on Rough Set Approach by Al Shalabi, Luai Abdel Lateef

“…Recently, different models were used to generate knowledge from vague and uncertain data sets such as induction decision tree, neural network, fuzzy logic, genetic algorithm, rough set theory, and others. …”
Get full text
Get full text

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.…”
Get full text
Get full text

An optimized variant of machine learning algorithm for datadriven electrical energy efficiency management (D2EEM) by Shamim, Akhtar

“…The scope of this study is tri folded, First, an exhaustive and parametric comparative study on a wide variety of machine learning algorithms is presented to evaluate the performance of machine learning algorithms in energy load prediction. …”
Get full text
Get full text

Unsupervised learning of image data using generative adversarial network by Rayner Alfred, Lun,, Chew Ye

“…Based on the results obtained, the GAN algorithm can learn the internal representation of data without labels and can act as good features extractor. …”
Get full text
Get full text
Get full text
Get full text

Next generation insect taxonomic classification by comparing different deep learning algorithms by Song-Quan Ong, Suhaila Ab. Hamid

“…The results show that different taxonomic ranks require different deep learning (DL) algorithms to generate high-performance models, which indicates that the design of an automated systematic classification pipeline requires the integration of different algorithms. …”
Get full text
Get full text
Get full text
Get full text
Get full text

Comparative analysis of three approaches of antecedent part generation for an IT2 TSK FLS by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

“…Since extreme learning machine is a non-iterative estimation procedure, it is faster than gradient-based algorithms which are iterative. …”
Get full text
Get full text

Small Dataset Learning In Prediction Model Using Box-Whisker Data Transformation by Lateh, Masitah bdul

“…From the previous studies, there are solutions to improve learning accuracy and predictive capability where some artificial data will be added to the system using artificial data generation approach. …”
Get full text
Get full text
Get full text
Get full text

Multi-Robot Learning with Bat Algorithm With Mutation (Bam) by Chandrathevan, Sathiamurthy

Get full text
Get full text

A fuzzy adaptive teaching learning-based optimization strategy for generating mixed strength t-way test suites by Din, Fakhrud

“…Owing to its proven performance in many other optimization problems, the adoption of the parameter-free Teaching Learning-based Optimization (TLBO) algorithm as a new t-way strategy is deemed useful. …”
Get full text
Get full text

A Reference Based Surface Defect Segmentation Algorithm For Automatic Optical Inspection System by Wong, Ze-Hao

“…However, present complex algorithms which are accurate require high processing power using a large size of learning dataset without labelling error. …”
Get full text
Get full text

Evaluating different machine learning models for predicting municipal solid waste generation: a case study of Malaysia by Latif S.D., Hazrin N.A.B., Younes M.K., Ahmed A.N., Elshafie A.

“…Therefore, one of the aims of this research was to investigate the use of machine learning algorithms and its benefits. …”

Functional link neural network with modified bee-firefly learning algorithm for classification task by Mohmad Hassim, Yana Mazwin

“…The standard learning method for tuning weights in FLNN is Backpropagation (BP) learning algorithm. …”
Get full text
Get full text
Get full text
Get full text

Comparison of Electricity Load Prediction Errors Between Long Short-Term Memory Architecture and Artificial Neural Network on Smart Meter Consumer by Salleh N.S.M., Suliman A., J�rgensen B.N.

A Hybrid of Ant Colony Optimization Algorithm and Simulated Annealing for Classification Rules by Rizauddin, Saian

“…In the first proposed algorithm, SA is used to optimize the rule's discovery activity by an ant. …”
Get full text
Get full text
Get full text
Get full text

Multi-step time series prediction using recurrent kernel online sequential extreme learning machine / Liu Zongying by Liu , Zongying

“…However, the problems with traditional offline and online learning algorithms in machine learning algorithms are usually faced with parameter dependency, concept drift handling problem, connectionless of neural net and unfixed reservoir. …”
Get full text
Get full text
Get full text