Search Results - (( panel optimization methods algorithm ) OR ( pattern detection mining algorithm ))

Effective mining on large databases for intrusion detection by Adinehnia, Reza, Udzir, Nur Izura, Affendey, Lilly Suriani, Ishak, Iskandar, Mohd Hanapi, Zurina

“…Data mining is a common automated way of generating normal patterns for intrusion detection systems. …”
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Outlier Detection Technique in Data Mining: A Research Perspective by Mansur, M. O., Md. Sap, Mohd. Noor

“…Finding ,removing and detecting outliers is very important in data mining, for example error in large databases can be extremely common, so an important property of a data mining algorithm is robustness with respect to outliers in the database. …”
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The application of neural network data mining algorithm into mixed pixel classification in geographic information system environment by Nanna Suryana, Herman

“…This , paper discusses the development of data mining and pattern recognition algorithm to handle the complexity of hyperspectral remote sensing images in Geographical Information Systems environment. …”
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Detecting Critical Least Association Rules In Medical Databases by Herawan, Tutut

“…We also employed our scalable algorithm called Significant Least Pattern Growth algorithm (SLP-Growth) to mine the respective association rules. …”
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Improvement anomaly intrusion detection using Fuzzy-ART based on K-means based on SNC Labeling by Zulaiha Ali Othman, Afaf Muftah Adabashi, Suhaila Zainudin, Saadat M. Al Hashmi

“…Data mining is a well-known artificial intelligence technique to build network intrusion detection systems. …”
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An ensemble learning method for spam email detection system based on metaheuristic algorithms by Behjat, Amir Rajabi

“…Even the smart people are unable to report an email as a spam when the spammer tries to defraud them. The aim of data mining is to search and find undetermined patterns in huge databases. …”
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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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Optimization of stiffened panel fatigue life by using finite element analysis by Mazlan, Shahan

“…Three optimization methods: screening, multi-objective genetic algorithm and adaptive multi-objective algorithm were adopted in this study. …”
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A Review of Unsupervised Machine Learning Frameworks for Anomaly Detection in Industrial Applications by Usmani, U.A., Happonen, A., Watada, J.

“…Without human input, these algorithms discover patterns or groupings in the data. …”
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Tracking student performance in introductory programming by means of machine learning by Khan I., Al Sadiri A., Ahmad A.R., Jabeur N.

Hybrid MPPT algorithm for mismatch photovoltaic panel application / Muhammad Iqbal Mohd Zakki by Mohd Zakki, Muhammad Iqbal

“…MATLAB/Simulink is used to develop, test, optimize, and verify the proposed hybrid MPPT algorithm, and PSO-PID tuning method, before embedded in the MPPT system for the hardware implementation as a research product. …”
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An Improved Artificial Dendrite Cell Algorithm for Abnormal Signal Detection by Mohamad Mohsin, Mohamad Farhan, Abu Bakar, Azuraliza, Hamdan, Abdul Razak, Abdul Wahab, Mohd Helmy

“…This causes the DCA fails to detect new data points if the pattern has distinct behavior from previous information and affects detection accuracy. …”
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Sequential pattern mining using personalized minimum support threshold with minimum items by Alias, Suraya, Razali, Mohd Norhisham, Tan, Soo Fun, Sainin, Mohd Shamrie

“…One of the challenges of Sequential Pattern Mining is finding frequent sequential patterns in a huge click stream data (web logs) since the data has the issue of a very low support distribution.By applying a Frequent Pattern Discovery technique, a sequence is considered as frequent if it occurs more than the minimum support (min sup) threshold value.The conventional method of assuming one min sup value is valid for all levels of k-sequence, may have an impact on the overall results or pattern generation. …”
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A hybrid interpretable deep structure based on adaptive neuro‑fuzzy inference system, decision tree, and K‑means for intrusion detection by Jia, Lu, Yin Chai, Wang, Chee Siong, Teh, Xinjin, Li, Liping, Zhao, Fengrui, Wei

“…For generating an interpretable deep architecture for identifying deep intrusion patterns, this study proposes an approach that combines ANFIS (Adaptive Network-based Fuzzy Inference System) and DT (Decision Tree) for interpreting the deep pattern of intrusion detection. …”
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An adaptive anomaly threshold in artificial dendrite cell algorithm by Mohamad Mohsin, Mohamad Farhan, Abu Bakar, Azuraliza, Hamdan, Abdul Razak

“…The dendrite cell algorithm (DCA) relies on the multi-context antigen value (MCAV) to determine the abnormality of a record by comparing it with anomaly threshold.In practice, the threshold is pre-determined before mining based on previous information and the existing MCAV is inefficient when expose to extreme values.This causes the DCA fails to detect unlabeled data if the new pattern distinct from previous information and reduces the detection accuracy.This paper proposed an adaptive anomaly threshold for DCA using the statistical cumulative sum (CUSUM) with the aim to improve its detection capability.In the proposed approach, the MCAV were normalized with upper CUSUM and the new anomaly threshold was calculated during run time by considering the acceptance value and min MCAV.From the experiments towards 12 datasets, the new version of DCA generated a better detection result than its previous version in term of sensitivity, specificity, false detection rate, and accuracy.…”
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Features selection for intrusion detection system using hybridize PSO-SVM by Tabaan, Alaa Abdulrahman

“…Electing the best set of features will help to improve the classifier predictions in terms of the normal and abnormal pattern. The simulation will be carried on WEKA tool, which allows us to call some data mining methods under JAVA environment. …”
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An improved artificial dendrite cell algorithm for abnormal signal detection by Mohamad Mohsin, Mohamad Farhan, Abu Bakar, Azuraliza, Hamdan, Abdul Razak, Abdul Wahab, Mohd Helmy

“…This causes the DCA fails to detect new data points if the pattern has distinct behavior from previous information and affects detection accuracy. …”
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Image clustering comparison of two color segmentation techniques by Subramaniam, Kavitha Pichaiyan

“…The clustering research is regarding the area of data mining and implementation of the clustering algorithms. …”
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Optimization variation for multiple heuristic approaches in solar tracking by Fam D.F., Koh S.P., Tiong S.K., Chong K.H.

Subjects: “…Genetic algorithm…”

Data Classification and Its Application in Credit Card Approval by Thai , VinhTuan

“…An analysis on the field of data mining is done to show how data mining, especially data classification, can help in businesses such as targeted marketing, credit card approval, fraud detection, medical diagnosis, and scientific work. …”
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