Search Results - (( data classification problems algorithm ) OR ( using identification using algorithm ))

Gas Identi cation by Using a Cluster-k-Nearest-Neighbor by Brahim Belhaouari, samir

“…We find 98.7% of accuracy in the classification of 6 different types of Gas by using K-means cluster algorithm and we find almost the same by using the new clustering algorithm.…”
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Application of Optimization Methods for Solving Clustering and Classification Problems by Shabanzadeh, Parvaneh

“…First we briefly give some data analysis background. Then a review of different methods currently available that can be used to solve clustering and classification problems is also given. …”
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Integrated combined layer algorithm of jamming detection and classification in manet / Ahmad Yusri Dak by Dak, Ahmad Yusri

“…The fourth stage is to design evaluation methodology of Max-Min Rule-Based Classification Algorithm using classifier model. Finally, both algorithms are validated against the findings in various literatures. …”
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Minimizing Classification Errors in Imbalanced Dataset Using Means of Sampling by Khan I., Ahmad A.R., Jabeur N., Mahdi M.N.

Improved TLBO-JAYA Algorithm for Subset Feature Selection and Parameter Optimisation in Intrusion Detection System by Aljanabi, Mohammad, Mohd Arfian, Ismail, Mezhuyev, Vitaliy

“…Many optimisation-based intrusion detection algorithms have been developed and are widely used for intrusion identification. …”
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Deep learning-based colorectal cancer classification using augmented and normalised gut microbiome data / Mwenge Mulenga by Mwenge , Mulenga

“…Second, to develop novel techniques that combine the strengths of normalisation, feature engineering and data augmentation to address the problem of dimensionality, feature dominance and sparsity in colorectal cancer identification based on gut microbiome data, using deep neural network algorithms. …”
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AN ACCURATE MODULATION CLASSIFICATION ALGORITHM FOR MULTIPLE-INPUT MULTIPLE-OUTPUT WIRELESS SYSTEMS by RIDA , MOHAMMAD BAHLOUL

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Plant recognition based on identification of leaf image using image processing / Nor Silawati Sha’ari by Sha’ari, Nor Silawati

“…NN such as Artificial Neural Network (ANN) and K-Nearest Neighbor (KNN) is trained in developing a classification system for agriculture purpose. ANN and KNN is applied to solve the problems in image analysis, pattern recognition and classification. …”
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Improved intrusion detection algorithm based on TLBO and GA algorithms by Aljanabi, Mohammad, Mohd Arfian, Ismail

“…Optimization algorithms are widely used for the identification of intrusion. …”
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Fingerprint feature extraction based discrete cosine transformation (DCT) by Chin Kim On, Paulraj M. Pandiyan, Sazali Yaacob, Azali Saudi

“…The extracted nCT data is used as input for the backpropagation neural network training for personal identification.…”
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Adaptive multi-parent crossover GA for feature optimization in epileptic seizure identification by Al-Sharhan, Salah, Bimba, Andrew

“…The classification was done using a Support Vector Machine (SVM). …”
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Fuzzy-based classifier design for determining the eye movement data as an input reference in wheelchair motion control by Mohd. Noor, Nurul Muthmainnah, Ahmad, Salmiah

“…Fuzzy logic is widely used in many complex and nonlinear systems for control, system identification and pattern recognition problems. …”
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Deep plant: A deep learning approach for plant classification / Lee Sue Han by Lee , Sue Han

“…Besides using solely a single leaf organ to recognize plant species, numerous studies have employed DL methods to solve multi-organ plant classification problem. …”
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Automatic identification of epileptic seizures from EEG signals using sparse representation-based classification by Sobhan Sheykhivand, Tohid Yousefi Rezaii, Zohreh Mousavi, Azra Delpak, Ali Farzamnia

“…A computerized seizure identification scheme can eradicate the above problems, assist clinicians, and benefit epilepsy research. …”
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Angle Based Protein Tertiary Structure Prediction Using Bees Optimization Algorithm by Al-Qattan, Zakaria Noor Aldeen Mahmood

“…WEKA program application was used for main chain angles (Phi and Psi) data classification. …”
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Named entity recognition using a new fuzzy support vector machine. by Mansouri, Alireza, Affendy, Lilly Suriani, Mamat, Ali

“…Some of the Machine learning algorithms used in NER methods are, support vector machine(SVM), Hidden Markov Model, Maximum Entropy Model (MEM) and Decision Tree. …”
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Classification Modeling for Malaysian Blooming Flower Images Using Neural Networks by Muhammad Ashraq, Salahuddin

“…The appearance of the image itself such as variation of lights due to different lighting condition, shadow effect on the object’s surface, size, shape, rotation and position, background clutter, states of blooming or budding may affect the utilized classification techniques. This study aims to develop a classification model for Malaysian blooming flowers using neural network with the back propagation algorithms. …”
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Smote and OVO multiclass method for multiple handheld placement gait identification on smartphone’s accelerometer by Abdul Raziff, Abdul Rafiez, Sulaiman, Nasir, Mustapha, Norwati, Perumal, Thinagaran

“…Besides that SMOTE is applied to the dataset to increase its sample data before the training procedure. For classification, OVO multiclass structure is proposed instead of using a single classifier algorithm. …”
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The Identification of hunger behaviour of lates calcarifer using k-nearest neighbour by Zahari, Taha, Mohd Azraai, M. Razman, N. F., Adnan

“…The clustered fish behaviour is then classified through k-Nearest Neighbour (k-NN) learning algorithm. Three different variations of the algorithm namely, fine, medium and coarse are assessed on its ability to classify the aforementioned fish hunger behaviour. …”
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Artificial Intelligent Based Arrhythmia Identification Via Single Lead Ecg Recording by Lim, Guo Jin

“…Final accuracy of 83.3% has been achieved during the training stage by using 300 training data. Final score of 0.7076 (Perfect score = 1) has been achieved when the 8528 data has been fetched into the developed neural network. …”
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