Search Results - (( data selection ((method algorithm) OR (path algorithm)) ) OR ( data normalization _ algorithm ))

Modeling and multi-objective optimal sizing of standalone photovoltaic system based on evolutionary algorithms by Ridha, Hussein Mohammed

“…Secondly, the modeling method of the proposed PV module is validated by experimental data. …”
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Algorithm enhancement for host-based intrusion detection system using discriminant analysis by Dahlan, Dahliyusmanto

“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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Optimal QoS aware multiple paths web service composition using heuristic algorithms and data mining techniques by Qtaish, Osama Kayed Taher

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A study on advanced statistical analysis for network anomaly detection by Ngadi, Md. Asri, Idris, Mohd. Yazid, Abdullah, Abd. Hanan

“…Anomaly detection algorithms model normal behavior. Anomaly detection models compare sensor data to normal patterns learned from the training data by using statistical method and try to detect activity that deviates from normal activity. …”
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Artificial immune system based on real valued negative selection algorithms for anomaly detection by Khairi, Rihab Salah

“…The Real-Valued Negative Selection Algorithms, which are the focal point of this research, generate their detector sets based on the points of self data. …”
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Weighted Sum-Dijkstra’s Algorithm in Best Path Identification based on Multiple Criteria by Ting, Kien Hua, Noraini Abdullah

“…Dijkstra’s Algorithm is a shortest path algorithm that considers a single criterion only. …”
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Integrating genetic algorithms and fuzzy c-means for anomaly detection by Chimphlee, Witcha, Abdullah, Abdul Hanan, Sap, Noor Md., Chimphlee, Siriporn, Srinoy, Surat

“…Traditional anomaly detection algorithms require a set of purely normal data from which they train their model. …”
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Improving Network Consistency and Data Availability Using Fuzzy C Mean Clustering Algorithm in Wireless Sensor Networks by Mujahid Tabassum

Dynamic Robust Bootstrap Algorithm for Linear Model Selection Using Least Trimmed Squares by Uraibi, Hassan Sami

“…The performances of the newly proposed methods are investigated extensively by real data sets and simulations study. …”
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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. …”
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Smart energy meter with adaptive communication data transfer algorithm for electrical energy monitoring by Ab Halim, Haizum Hanim

“…Thus, in this thesis, a new Smart Energy Meter (SEM) with adaptive data transfer algorithm is designed to accommodate the problem. …”
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Spectral discrimination and index development of roofing materials and conditions using field spectroscopy and worldview-3 satellite image by Samsudin, Sarah Hanim

“…Three feature selection algorithms of Genetic Algorithm (GA), Support Vector Machine (SVM) and Random Forest (RF) were used to select the most significant wavelengths since the algorithms works well with large size of data and widely applied for feature selection of hyperspectral remote sensing data. …”
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An enhancement of path selection to cluster head based on multi-hop routing in two-tier wireless sensor network by Wan Isni Sofiah, Wan Din, Asyran Zarizi, Abdullah, Razulaimi, Razali, Ahmad Firdaus, Zainal Abidin, Salwana, Mohamad, Eh Phon, Danakorn Nincarean, Cik Feresa, Mohd Foozy

“…Currently, the data transmission from sensor nodes to the cluster head uses a single hop which consumes more energy; thus, in this paper the enhancement of previous algorithm, which is MAP, the data transmission will use several paths to reach the cluster head. …”
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Swarm negative selection algorithm for electroencephalogram signals classification by Sahel Ba-Karait, Nasser Omer, Shamsuddin, Siti Mariyam, Sudirman, Rubita

“…The SNS classification model use negative selection and PSO algorithms to form a set of memory Artificial Lymphocytes (ALCs) that have the ability to distinguish between normal and epileptic EEG patterns. …”
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Fault diagnostic algorithm for precut fractionation column by Heng, H. Y., Ali, Mohamad Wijayanuddin, Kamsah, Mohd. Zaki

“…Hazard and Operability Study (HAZOP) is used to support the diagnosis task. The algorithm has been successful in detecting the deviations of each variable by testing the data set. …”
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A case study of microarray breast cancer classification using machine learning algorithms with grid search cross validation by Mohd Ali, Nursabillilah, Besar, Rosli, Ab Aziz, Nor Azlina

“…In this work, simple machine learning methods are used to classify breast cancer microarray data to normal and relapse. …”
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Design of radix-4 single path delay fast fourier transform processor with genetic algorithms optimization by Pang, Jia Hong

“…The genetic algorithms is proven to be a very effective method in optimization by using the way imitating natural process of living beings such as crossover, mutation and selection. …”
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Robust variable selection methods for large- scale data in the presence of multicollinearity, autocorrelated errors and outliers by Uraibi, Hassan S.

“…The Reweighted Multivariate Normal (RMVN) algorithm is incorporated in the algorithm of the BAE-Net. …”
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Transient analysis for leak signature identification based on Hilbert Huang transform and integrated kurtosis algorithm for z-notch filter technique by Muhammad Hanafi, Yusop

“…However, this method has the difficulty in selecting the suitable IMF for the next data post-processing method, which is Hilbert Transform (HT). …”
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Simulation algorithm of bayesian approach for choice-conjoint model by Zulhanif

“…Generally in Choice-Conjoint method the Multinomial Logit Model (MNL) is normally used to analyze choice conjoint data, but the MNL has some serious limitations. …”
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