Search Results - (( java implication based algorithm ) OR ( set generation learning algorithm ))

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

“…Also, the proposed models for learning in data sets generated the classification rules faster than other methods. …”
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

A Hybrid Rough Sets K-Means Vector Quantization Model For Neural Networks Based Arabic Speech Recognition by Babiker, Elsadig Ahmed Mohamed

“…Classification rules were generated from training feature vectors set, and a modified form of the standard voter classification algorithm, that use the rough sets generated rules, was applied. …”
Get full text
Get full text

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

“…Benchmark data sets from various fields were used to test the proposed algorithms. …”
Get full text
Get full text
Get full text
Get full text

A low dispersion probabilistic roadmaps (LD-PRM) algorithm for fast and efficient sampling-based motion planning by Khaksar W., Hong T.S., Khaksar M., Motlagh O.

“…In this paper, we propose a new learning strategy for a probabilistic roadmap (PRM) algorithm. …”

The new efficient and accurate attribute-oriented clustering algorithms for categorical data by Qin, Hongwu

“…Four real-life data sets obtained from University of California Irvine (UCI) machine learning repository and ten synthetically generated data sets are used to evaluate MGR and IG-ANMI algorithms, and other four algorithms are used to compare with these two algorithms. …”
Get full text
Get full text

A new technique for improving the dispersion of a set of samples. Application in multi-query motion planning by Khaksar W., Hong T.S., Sahari K.S.B.M., Khaksar M.

“…For measuring the uniformity of the generated samples, a new algorithm was created to measure the dispersion of a set of samples based on any desired resolution. …”

Tap Settings Optimization in Power Systems: Economic Efficiency Enhancement Through Cuckoo Search Algorithm While Ensuring Voltage Stability by Raizal N.I., Mansor M.H., Musirin I., Shaaya S.A., Ismail S.A., Ismail N.L.

Subjects:

Short-Term forecasting of floating photovoltaic power generation using machine learning models by Mohd Herwan, Sulaiman, Mohd Shawal, Jadin, Zuriani, Mustaffa, Mohd Nurulakla, Mohd Azlan, Hamdan, Daniyal

“…The dataset was divided into a training set (first five days) and a testing set (remaining two days), and five machine learning models—Neural Networks (NN), Random Forest (RF), Extreme Learning Machine (ELM), Support Vector Regression (SVR), and Long Short-Term Memory (LSTM)—were employed. …”
Get full text
Get full text
Get full text

Development of a Bioinspired optimization algorithm for the automatic generation of multiple distinct behaviors in simulated mobile robots by Hanafi Ahmad Hijazi, Patricia Anthony

“…A simulated Khepera robot is evolved by a Pareto-frontier Differential Evolution (POE) algorithm, and learned through a 3-layer feed-forward artificial neural network, attempting to simultaneously fulfill two conflicting objectives of maximizing robot phototaxis behavior while minimizing the neural network's hidden neurons by generating a Pareto optimal set of controllers. …”
Get full text
Get full text

Optimal parameters of an ELM-based interval type 2 fuzzy logic system: a hybrid learning algorithm by Hassan, S., Khanesar, M.A., Jaafar, J., Khosravi, A.

“…A disadvantage of ELM is the random generation of its hidden neuron that causes additional uncertainty, in both approximation and learning. …”
Get full text
Get full text

A low dispersion probabilistic roadmaps (LD-PRM) algorithm for fast and efficient sampling-based motion planning by Khaksar, Weria, Tang, Sai Hong, Khaksar, Mansoor, Motlagh, Omid Reza Esmaeili

“…In this paper, we propose a new learning strategy for a probabilistic roadmap (PRM) algorithm. …”
Get full text
Get full text
Get full text

MaxD K-Means: A clustering algorithm for auto-generation of centroids and distance of data points in clusters by Wan Maseri, Wan Mohd, Beg, Abul Hashem, Herawan, Tutut, Fazley Rabbi, Khandakar

“…In this paper, we propose a clustering technique called MaxD K-Means clustering algorithm. MaxD K-Means algorithm auto generates initial k (the desired number of cluster) without asking for input from the user. …”
Get full text
Get full text
Get full text

An Apriori-based Data Analysis on Suspicious Network Event Recognition by Jian, Z., Sakai, H., Watada, J., Roy, A., Hassan, M.H.B.

“…Apriori-based rule generators, which are powered by the DIS-Apriori algorithm and the NIS-Apriori algorithm, are applied to analyze the data sets available in the IEEE BigData 2019 Cup: Suspicious Network Event Recognition. …”
Get full text
Get full text

A Case Study of Using Long Short-Term Memory (LSTM) Algorithm in Solar Photovoltaic Power Forecasting by Lee Chin, Kho, Sze Song, Ngu, Annie, Joseph, Siti Kudnie, Sahari, Kuryati, Kipli, R., Rulaningtyas

“…The results show that the deep learning algorithm provides reliable forecasting results.…”
Get full text
Get full text
Get full text
Get full text

Automatic email classification system / Phang Siew Ting by Phang , Siew Ting

“…The algorithms learn to classify emails based on it textual contents, and subsequently assign individual emails into a predefined set of categories or bins in accordance with the preferences of a user. …”
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

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

“…However, to build a robust prediction model, the learning process from the training set are advised to have many samples. …”
Get full text
Get full text
Get full text
Get full text

Algorithm as a problem solving technique for teaching and learning of the Malay language by Nazir, Faridah, Jano, Zanariah, Omar, Norliza

“…This conceptual teaching and learning algorithm was conducted in five steps namely the induction set; step 1; step 2; step 3; and enrichment and recovery. …”
Get full text
Get full text
Get full text

Frequent Lexicographic Algorithm for Mining Association Rules by Mustapha, Norwati

“…The scale-up experiment showed that the proposed algorithm is more scalable than the other existing algorithms. …”
Get full text
Get full text