Search Results - (( pattern classifications using algorithm ) OR ( using case data algorithm ))

Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

“…It involves development of Max-Min Rule-Based Classification Algorithm. The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. …”
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Case study : an effect of noise in character recognition system using neural network by Mohamad, Esmawaty

“…Neural networks are useful tools for solving many type of problems. These problems may be characterized as mapping(including pattern association and pattern classification), clustering and constrained optimization. …”
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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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The analysis of road traffic fatality pattern for Selangor, Malaysia case study by Radzuan, N. Q., Mohd Hasnun Ariff, Hassan, Abu Kassim, K. A., Ab. Rashid, A. A., Intan Suhana, Mohd Razelan, Nur Aqilah, Othman

“…Supervised machine learning algorithm in Orange data mining software was considered in this analysis. …”
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Data Mining for Building Neural Protein Sequence Classification Systems with Improved Performance by Wang, Dianhui, Lee, Nung Kion, Dillon, Tharam S.

“…In contrast, in this paper we use a generalized radial basis function (GRBF) neural network architecture 'that generates fuzzy classification rules that could he used for further knowledge discovery. …”
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Modern fuzzy min max neural networks for pattern classification by Al Sayaydeh, Osama Nayel Ahmad

“…Among these algorithms, Fuzzy Min Max (FMM) neural network algorithm has been proven to be one of the premier neural networks for undertaking the pattern classification problems. …”
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Hybrid Classification Algorithm For Denial Of Service Attack Detection Using Rough Set Theory And Artificial Immune by Fatin Norsyafawati, Mohd Sabri

Feature extraction and classification :a case study of classifying a simulated digital mammogram images using self-organizing maps (som) by Lau, Leh Teen.

“…A set of training input data is used to train SOM. The accuracy of classification performance was acquired. …”
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Random Undersampling on Imbalance Time Series Data for Anomaly Detection by Saripuddin M., Suliman A., Syarmila Sameon S., Jorgensen B.N.

Classification Analysis Of The Badminton Five Directional Lunges by Ho, Zhe Wei

“…Lunge type patterns were related to ID and GT. Conclusively, the identity, game reaction time and type of lunge were found being the key determinants for badminton lunge classification accounting for highest classification accuracy in REP Tree algorithm.…”
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Modified word representation vector based scalar weight for contextual text classification by Abbas Saliimi, Lokman

“…In addition, a contextual text classification experiment is conducted using benchmarked datasets to assess the performance of the modified word vectors in the targeted classification task. …”
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Twofold Integer Programming Model for Improving Rough Set Classification Accuracy in Data Mining. by Saeed, Walid

“…The accuracy for rules and classification resulted from the TIP method are compared with other methods such as Standard Integer Programming (SIP) and Decision Related Integer Programming (DRIP) from Rough Set, Genetic Algorithm (GA), Johnson reducer, HoltelR method, Multiple Regression (MR), Neural Network (NN), Induction of Decision Tree Algorithm (ID3) and Base Learning Algorithm (C4.5); all other classifiers that are mostly used in the classification tasks. …”
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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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A Framework For Classification Software Security Using Common Vulnerabilities And Exposures by Hassan, Nor Hafeizah

“…This inclusive of the investigation of vulnerability classification objectives,processes,classifiers and focus domains among prominent framework.Final step is to construct the framework by establishing the formal presentation of the vulnerability classification algo-rithm.The validation process was conducted empirically using statistical method to assess the accuracy and consistency by using the precision and recall rate of the algorithm on five data sets each with 500 samples.The findings show a significant result with precision's error rate or p value is between 0.01 and 0.02 with error rate for recall's error rate is between 0.02 and 0.04.Another validation was conducted to verify the correctness of the classification by using expert opinions,and the results showed that the ambiguity of several cases were subdue. …”
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Deep plant: A deep learning approach for plant classification / Lee Sue Han by Lee , Sue Han

“…They look for the procedures or algorithms that maximize the use of leaf databases for plant predictive modelling, but this results in leaf features which are liable to change with different leaf data and feature extraction techniques. …”
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Classification Of Gender Using Global Level Features In Fingerprint For Malaysian Population by Abdullah, Siti Fairuz

“…These four classifiers are used in the data mining task with five test cases each in order to find the accuracies of the gender classification. …”
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Simple quantum circuit for pattern recognition based on nearest mean classifier by Mahmoud Ahmed, Gharib Subhi, Messikh Azeddine, Azeddine

“…In our case the hyperplane is found using projections and rotations on the Bloch sphere.…”
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Walking gait event detection based on electromyography signals using artificial neural network by Nazmi, Nurhazimah, Abdul Rahman, Mohd Azizi, Yamamoto, Shin Ichiroh, Ahmad, Siti Anom

“…Eight subjects that participated in this study were divided into two categories namely, learned (first seven subjects) and unlearned data (the remaining one subject). It was observed that Levenberg-Marquardt algorithm with five time domain features performed better than other features with an average percentage of classification accuracy of 87.4%. …”
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Adaptive Non-Stationary Cardiac Signals Identification using an Augmented MLP Network by Asirvadam , Vijanth Sagayan, McLoone, Sean

“…Modeling or representing a signal of a system (in this case biomedical system), can be viewed as a filtering technique which intends to reduce white noise or uncorrelated noise, where modeled data is used for proceeding tasks such as feature extractions and classification techniques. …”
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Firearm recognition based on whole firing pin impression image via backpropagation neural network by Ahmad Kamaruddin, Saadi, Md Ghani, Nor Azura, Liong, Choong-Yeun, Jemain, Abdul Aziz

“…A two-layer 6-7-5 connections BPNN of sigmoid/linear transfer functions with ‘trainlm’ algorithm was found to yield the best classification result using cross-validation, where 96% of the images were correctly classified according to the pistols used. …”
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