Search Results - (( basic identification system algorithm ) OR ( code classification modelling algorithm ))

Modelling of clinical risk groups (CRGs) classification using FAM by Mohd. Asi, Salina, Saad, Puteh

“…FAM is a fast learning algorithm and used less epoch training [4]. Based on its performance in doing the classification, FAM is theoretically suitable to do the CRGs classification. …”
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Network Traffic Classification Analysis on Differentiated Services Code Point Using Deep Learning Models for Efficient Deep Packet Inspection by Ahmed Khan, Fazeel, Abubakar, Adamu

“…This study develops and analyze using neural network-based models for effective classification of data packets using the DSCP header field. …”
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Image classification based on sparse-coded features using sparse coding technique for aerial imagery: a hybrid dictionary approach by Qayyum A., Saeed Malik A., Saad N.M., Iqbal M., Abdullah M.F., Rasheed W., Abdullah T.A.B.R., Bin Jafaar M.Y.

Recursive Subspace Identification Algorithm Using The Propagator Based Method by Jamaludin, Irma Wani, Abdul Wahab, Norhaliza

“…Basically, subspace identifications are based on algorithms from numerical algebras which are the QR decomposition and Singular Value Decomposition (SVD). …”
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Adaptive Linear System Identification over Simulated Wireless Environment by Elamin, Musab Jabralla Omer Elamin

“…Wireless technologies have become one of the basic industrial pillars, whereas system identification represents an important tool in many practical engineering circumstances and thus sooner or later both wireless technologies and system identification should be linked together in sense of having an identifier that is able to reliably identify a system over wireless links. …”
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System identification using Extended Kalman Filter by Alias, Ahmad Hafizi

“…System identification is getting more intensive from researcher to develop an algorithm with work efficiently and more accurate. …”
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Genetic algorithm fuzzy logic for medical knowledge-based pattern classification by Tan, Chin Hooi, Tan, Mei Sze, Chang, Siow Wee, Yap, Keem Siah, Yap, Hwa Jen, Wong, Shen Yuong

“…The proposed algorithm was applied and tested in four critical illness datasets in medical knowledge pattern classification. …”
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Scene classification for aerial images based on CNN using sparse coding technique by Qayyum, A., Malik, A.S., Saad, N.M., Iqbal, M., Faris Abdullah, M., Rasheed, W., Rashid Abdullah, T.A., Bin Jafaar, M.Y.

“…Recent developments include several approaches and numerous algorithms address the task. This article proposes a convolutional neural network (CNN) approach that utilizes sparse coding for scene classification applicable for HRRS unmanned aerial vehicle (UAV) and satellite imagery. …”
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Machine learning-based enhanced deep packet inspection for IP packet priority classification with differentiated services code point for advance network management by Khan, Fazeel Ahmed, Abubakar, Adamu

“…This study presents an approach to enhance intelligent packet forwarding priority classification on Differentiated Services Code Point (DSCP), leveraging classifiers from machine learning algorithms for Deep Packet Inspection (DPI). …”
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Voltage stability margin identification using evolution programming learning algorithm / Zamzuhairi Darus by Darus, Zamzuhairi

“…Voltage stability problems have been one of the major concerns for electric utilities as a result of a system heavy loading. This project proposed on an investigation on the voltage stability margin identification using evolution programming learning algorithm. …”
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Scene classification for aerial images based on CNN using sparse coding technique by Qayyum A., Malik A.S., Saad N.M., Iqbal M., Faris Abdullah M., Rasheed W., Rashid Abdullah T.A., Bin Jafaar M.Y.

An improved plant identification system by Fuzzy c-means bag of visual words model and sparse coding by Safa, Soodabeh, Khalid, Fatimah

“…Current work adopts the Fuzzy c-means Bag of Visual Words model and sparse coding for plant identification. …”
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Malware Classification and Detection using Variations of Machine Learning Algorithm Models by Andi Maslan, Andi Maslan, Abdul Hamid, Abdul Hamid

“…The research stage starts from pre-Processing, extraction, feature selection and classification processes and performance testing. Training and testing data in the study used a mixed model, namely data division, split model and cross validation. …”
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Object-Oriented Programming semantics representation utilizing agents by Mohd Aris, Teh Noranis

“…The algorithm requires source codes comparison based on keyword similarity to extract the words that exist in the two related source codes. …”
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Genetic algorithm fuzzy logic for medical knowledge-based pattern classification by Tan C.H., Tan M.S., Chang S.-W., Yap K.S., Yap H.J., Wong S.Y.

“…The proposed algorithm was applied and tested in four critical illness datasets in medical knowledge pattern classification. …”

Cross-project software defect prediction by Bala, Yahaya Zakariyau, Abdul Samat, Pathiah, Sharif, Khaironi Yatim, Manshor, Noridayu

“…Through this work, it was discovered the majority of the selected studies used machine learning techniques as classification algorithms, and 64% of the studies used the combination of Object-Oriented (OO) and Line of Code (LOC) metrics. …”
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Multi-class classification automated machine learning for predicting earthquakes using global geomagnetic field data by Qaedi, Kasyful, Abdullah, Mardina, Yusof, Khairul Adib, Hayakawa, Masashi, Zulhamidi, Nur Fatin Irdina

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Hazard identification on fractionation column using rule based expert system by Mohd Yunus, Mohd Yusri, Ali, Mohamad Wijayanuddin

“…The algorithm is found applicable for any of process system, however the expert system developed is only limited to the application for fractionation column of oleo chemical plant.…”
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Model Identification Using Neuro-Fuzzy Approach by Lemma, T.A.

“…In Sect. 3.3, basic theory of neural networks and fuzzy systems are elaborated. …”
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Model Identification Using Neuro-Fuzzy Approach by Lemma, T.A.

“…In Sect. 3.3, basic theory of neural networks and fuzzy systems are elaborated. …”
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