Search Results - (( pattern mining algorithm ) OR ((( pattern bees algorithm ) OR ( case research algorithm ))))*

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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Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Dhany, Saputra

“…Sequential pattern mining is a new branch of data, mining science that solves inter-transaction pattern mining problems. …”
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Sequential pattern mining using PrefixSpan with pseudoprojection and separator database by Saputra, D., Rambli, D.R.A., Foong, Oi Mean

“…Sequential pattern mining is a new branch of data mining science that solves inter-transaction pattern mining problems. …”
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Separator Database and SPM Tree Framework for Mining Sequential Patterns Using Prefixspan with Pseudoprojection by Saputra , Dhany, Rambli, Dayang R.A., Foong, Oi Mean

“…Sequential pattern mining is a new branch of data, mining science that solves inter-transaction pattern mining problems. …”
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Data mining for structural damage identification using hybrid artificial neural network based algorithm for beam and slab girder / Meisam Gordan by Meisam , Gordan

“…In the modeling phase, amongst all DM algorithms, the applicability of machine learning, artificial intelligence and statistical data mining techniques were examined using Support Vector Machine (SVM), Artificial Neural Network (ANN) and Classification and Regression Tree (CART) to detect the hidden patterns in vibration data. …”
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Facilitating resource allocation decision through Bibliomining: the case of UTM's library / Md Razib Karno by Karno, Md Razib

“…With nearly 1 million records of collection in various formats, the Library of Universiti Teknologi Malaysia has been chosen as the case study for the research. The data mining technique was adopted to explore the relationship among statistically patterned and clustered bibliographic data. …”
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Cyber fraud profiling with routine activity theory using data mining techniques / Sunardi, Abdul Fadlil and Nur Makkie Perdana Kusuma by -, Sunardi, -, Abdul Fadlil, Perdana Kusuma, Nur Makkie

“…This study aims to create a cyber-fraud pattern based on a profile created from RAT. This research is expected to be input for internet users in Indonesia, especially IM users such as Instagram, Facebook, WhatsApp, and Telegram. …”
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Development of a Web Access Control Technique Based User Access Behavior by Abdelrahman, Selmaelsheikh

“…A set of algorithms is used for mining user access behavior, preprocessing tasks for data preparation, association rules for defining the rules that describe the correlation between web user access transaction entries patterns, and sequential pattern discovery for finding the sequences of the web user access transaction entries pattern using Prefixspan (Pattern growth via frequent sequence lattice) algorithms. …”
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An Integrated Principal Component Analysis And Weighted Apriori-T Algorithm For Imbalanced Data Root Cause Analysis by Ong, Phaik Ling

“…However, frequent pattern mining (FPM) using Apriori-like algorithms and support-confidence framework suffers from the myth of rare item problem in nature. …”
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

“…This research opens a wide range of future work to be considered, which includes applying the proposed method in other areas such as web mining, text mining or multimedia mining; and extending the proposed approach to work in parallel computing in data mining.…”
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Predicting stroke using ant colony optimization algorithm / Azfaruddin Azri and Rizauddin Saian by Azri, Azfaruddin, Saian, Rizauddin

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Modifying iEclat algorithm for infrequent patterns mining by Julaily Aida, J., Mustafa, M.

“…This paper proposes an enhancement algorithm based on iEclat algorithms for mining infrequent pattern.…”
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Partitional clustering algorithms for highly similar and sparseness Y-Short Tandem Repeat Data / Ali Seman by Seman, Ali

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Modifying iEclat algo ithm for infrequent patterns mining by Julaily Aida, Jusoh, Mustafa, Man

“…This paper proposes an enhancement algorithm based on iEclat algorithms for mining infrequent pattern.…”
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Flood Routing in River Reaches Using a Three-Parameter Muskingum Model Coupled with an Improved Bat Algorithm by Farzin, Saeed, Singh, Vijay, Karami, Hojat, Farahani, Nazanin, Ehteram, Mohammad, Kisi, Ozgur, Allawi, Mohammed Falah, Mohd, Nuruol Syuhadaa, El-Shafie, Ahmed

“…Seven performance indexes were examined to evaluate the performance of the proposed Muskingum model integrated with IBA, with other models that were also based on the Muskingum Model with three-parameters but utilized different optimization algorithms. The results for the Wilson flood showed that the proposed model could reduce the Sum of Squared Deviations (SSD) value by 89%, 51%, 93%, 69%, and 88%, compared to the Genetic Algorithm (GA), Particle Swarm Optimization (PSO) algorithm, Pattern Search (PS) algorithm, Harmony Search (HS) algorithm, and Honey Bee Mating Optimization (HBMO), respectively. …”
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Web based clustering tool using K-MEAN++ algorithm / Muhammad Nur Syazwanie Aznan by Aznan, Muhammad Nur Syazwanie Aznan

“…Cluster analysis is one of the data mining task that are widely used in many area to extracting, grouping data with similar attribute in order to uncover the hidden pattern and meaning in the data. …”
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Partitional clustering algorithms for highly similar and sparseness y-short tandem repeat data / Ali Seman by Seman, Ali

“…The idea was incorporated into a new algorithm called, k-Approximate Modal Haplotypes (&-AMH) algorithm. …”
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Performance of IF-Postdiffset and R-Eclat Variants in Large Dataset by Julaily Aida, Jusoh, Wan Aezwani, Wan Abu Bakar, Mustafa, Man

“…The multiple variants in the R-Eclat algorithm generate varied performances in infrequent mining patterns. …”
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Efficient prime-based method for interactive mining of frequent patterns. by Mohammad Hossein, Nadimi Shahraki, Mustapha, Norwati, Sulaiman, Md. Nasir, Mamat, Ali

“…Since rerunning mining algorithms from scratch is very costly and time-consuming, researchers have introduced interactive mining of frequent patterns. …”
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Web user navigation pattern mining approach based on graph partitioning algorithm. by Jalali, Mehrdad, Mustapha, Norwati, Mamat, Ali, Sulaiman, Md. Nasir

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