Search Results - (( java implementation drops algorithm ) OR ( pattern extraction efficient algorithm ))

Improving mining efficiency: A new scheme for extracting association rules by Said, Aiman Moyaid, Dominic, P D D., Abdullah, Azween

“…In the age of information technology, the amount of accumulated data is tremendous. Extracting the association rule from this data is one of the important tasks in data mining.Most of the existing association rules in algorithms typically assume that the data set can fit in the memory.In this paper, we propose a practical and effective scheme to mine association rules from frequent patterns, called Prefixfoldtree scheme (PFT scheme).The original dataset is divided into folds, and then from each fold the frequent patterns are mined by using the tree projection approach.These frequent patterns are combined into one set and finally interestingness constraints are used to extract the association rules.The experiments will be conducted to illustrate the efficiency of our scheme.…”
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Hand blood vessels pattern recognition by Tan, Xuan Qing

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Agarwood oil grade clustering of aquilaria malaccensis species using Extraction by GC-MS analysis: Efficient KNN algorithm based on patterns visualization of two-dimensional graph by Siti Mariatul Hazwa, Mohd Huzir, Anis Hazirah ‘Izzati H., Al-Hadi, Amir Hussairi, Zaidi, Nurlaila F., Ismail, Zakiah, Mohd Yusoff, Saiful Nizam, Tajuddin, Mohd Nasir, Taib

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Anti-stammering algorithm with adapted multi-layer perceptron by Ali Bashar Hussein, Al-Nima, Raid Rafi Omar, Han, Tingting

“…This algorithm includes an effective feature extraction approach and an adapted classifier. …”
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An efficient fuzzy C-least median clustering algorithm by Mallik, Moksud Alam, Zulkurnain, Nurul Fariza, Nizamuddin, Mohammed Khaja, Aboosalih, K C

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Data mining using genetic algorithm in finance data / A. Noor Latiffah and A. B. Nordin by Latiffah, A. Noor, Nordin, A. B.

“…Data mining can discover patterns or rules from a vast volume of data. This patterns or rules may help to develop better decision-making process. …”
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Modeling of vehicle trajectory clustering based on LCSS for traffic pattern extraction by Choong, Mei Yeen, Lorita Angeline, Chin, Renee Ka Yin, Yeo, Kiam Beng, Teo, Kenneth Tze Kin

“…These behavioural manoeuvres are useful for interpreting the indepth study of traffic pattern in a traffic network. Hence, with the advancement of the available vehicle tracking system, vehicle trajectory dataset is selected as suitable candidate input for the traffic pattern extraction. …”
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Feature extraction: hand shape, hand position and hand trajectory path by Bilal, Sara Mohammed Osman Saleh, Akmeliawati, Rini

“…Algorithms have been developed for extracting these features after segmenting the head and the two hands. …”
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Pattern Classification of Human Epithelial Images by Mohd Isa, Mohd Fazlie

“…First of all, image enhancement will take part in order to boost efficiency of algorithm by implementing some of the adjustment and filtering technique to increase the visibility of image. …”
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Solar photovoltaic system based on perturb and observe maximum power point tracking with trapezoidal rule approach under partial shading conditions by Altwallbah, Neda Mahmod Mohammad.

“…The second is to propose a hybrid MPPT algorithm based on modified P&O algorithm assisted by Extremum Seeking Control (ESC) approach, in order to maximize the extracted PV power under complex PSC. …”
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Feature extraction for face recognition via Active Shape Model (ASM) and Active Appearance Model (AAM) by Iqtait, M., Mohamad, F.S., Mamat, M.

“…Cootes proposed a Multi Resolution Active Shape Models (ASM) algorithm, which could extract specified shape accurately and efficiently. …”
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A new classification model for online predicting users' future movements by Jalali, Mehrdad, Mustapha, Norwati, Mamat, Ali, Sulaiman, Md. Nasir

“…The WUM can model user behavior and, therefore, to forecast their future movements by mining user navigation patterns. To provide online prediction efficiently, we advance architecture for online predicting in web usage mining system by proposing novel model based on Longest Common Subsequence algorithm for classifying user navigation patterns. …”
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EMG motion pattern classification through design and optimization of neural network by Ahsan, Md. Rezwanul, Ibrahimy, Muhammad Ibn, Khalifa, Othman Omran

“…The EMG signals obtained for different kinds of hand motions, which further denoised and processed to extract the features. Extracted time and time-frequency based feature sets are used to train the neural network. …”
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Cabbage disease detection system using k-NN algorithm by Mohamad Ainuddin Sahimat

“…Then, the segmented cabbage sample will use the GLCM method for feature extraction. It is a method of extracting second-order statistical texture features to detect diseases more efficiently. …”
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The discovery of Top-K DNA frequent patterns with approximate method / Nittaya Kerdprasop and Kittisak Kerdprasop by Kerdprasop, Nittaya, Kerdprasop, Kittisak

“…Top-k frequent pattern discovery is indeed an association analysis concerning automatic extraction of the k most correlated and interesting patterns from large databases. …”
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EMG motion pattern classification through design and optimization of Neural Network by Md. Rezwanul, Ahsan, Muhammad Ibn, Ibrahimy, Othman Omran, Khalifa

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Development of a scaled conjugate gradient algorithm for significant RF neural signal processing by Mohd Norden, Muhammad Farid Akmal, Mohd Isa, Roshakimah, Mohd Isa, Mohd Roshalizi, S. Abdul Kadir, Ros Shilawani, Md Azli, Muhammad Hariz, Muhammad Akram, Amir Syarif

“…Artificial Neural Networks (ANN) are computational models inspired by the human brain, capable of recognizing patterns and making predictions. Scale Conjugate Gradient (SCG) algorithm is an efficient training method for ANN that accelerates the learning process and improves output accuracy. …”
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Facial image retrieval on semantic features using adaptive mean genetic algorithm by Shnan, Marwan Ali, Rassem, Taha H., Nor Saradatul Akmar, Zulkifli

“…The performance matrix of the AMGA was compared to those of particle swarm optimization algorithm (PSO) and genetic algorithm (GA) and found to perform better; thus, proving its efficiency.…”
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Data normalization techniques in swarm-based forecasting models for energy commodity spot price by Yusof, Yuhanis, Mustaffa, Zuriani, Kamaruddin, Siti Sakira

“…Data mining is a fundamental technique in identifying patterns from large data sets.The extracted facts and patterns contribute in various domains such as marketing, forecasting, and medical.Prior to that, data are consolidated so that the resulting mining process may be more efficient.This study investigates the effect of different data normalization techniques.which are Min-max, Z-score and decimal scaling, on Swarm-based forecasting models.Recent swarm intelligence algorithms employed includes the Grey Wolf Optimizer (GWO) and Artificial Bee Colony (ABC).Forecasting models are later developed to predict the daily spot price of crude oil and gasoline.Results showed that GWO works better with Z-score normalization technique while ABC produces better accuracy with the Min-Max.Nevertheless, the GWO is more superior than ABC as its model generates the highest accuracy for both crude oil and gasoline price.Such a result indicates that GWO is a promising competitor in the family of swarm intelligence algorithms.…”
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Semantic-k-NN algorithm: An enhanced version of traditional k-NN algorithm by Ali, M., Jung, L.T., Abdel-Aty, A.-H., Abubakar, M.Y., Elhoseny, M., Ali, I.

“…Ultimately, Sk-NN is to elevate the ML performance in pattern extraction and labeling in the big data context. …”
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