Search Results - (( data normalization _ algorithm ) OR ( parameter classification using algorithm ))

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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Whale optimization algorithm based on tent chaotic map for feature selection in soft sensors by AlRijeb, Mothena Fakhri Shaker, Othman, Mohammad Lutfi, Ishak, Aris, Hassan, Mohd Khair, Albaker, Baraa Munqith

“…Selecting the relevant features from the data leads to better classification results. Optimization algorithms are successfully applied in the feature selection task in many systems. …”
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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

“…Spectral index of NDCCI and NDMCI found to be effective in providing roof degradation status map in effective time-manner and parameter-free algorithm compared to normal supervised classification scheme. …”
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Water Quality Evaluation and Analysis by Integrating Statistical and Machine Learning Approaches by Amar Lokman, Wan Zakiah Wan Ismail, Nor Azlina Ab Aziz

Analyzing land surface temperature in response to massive urbanization by using single window algorithm in Penang Island / Ainna Naeemah Zainal Abidin by Zainal Abidin, Ainna Naeemah

“…This study involved the Landsat 5 TM and Landsat 8 OLI satellite imagery to be used as data to achieve the aim. Apart from classification process. …”
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Handgrip strength evaluation using neuro fuzzy approach by Seng, W.C., Chitsaz, M.

“…The fuzzy model based on the membership function, fed in by the neural network will intelligently classify the data. The results indicate that the classification accuracy of normal and pathological patients are 90 and 75 respectively. …”
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The effect of pre-processing techniques and optimal parameters on BPNN for data classification by HUSSEIN, AMEER SALEH

“…The Min-Max, Z-Score, and Decimal Scaling Normalization pre-processing techniques were analyzed. …”
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Detection of proliferative diabetic retinopathy in fundus images using convolution neural network by Hasliza, Abu Hassan, Marzuqi, Yaakob, Sasni, Ismail, Juwairiyyah, Abd Rahman, Izyani, Mat Rusni, Azlee, Zabidi, Ihsan, Mohd Yassin, Nooritawati, Md Tahir, Suraiya, Mohamad Shafie

“…This study consisted three objectives that included the execution of two pre-processing techniques on the data-set which were resizing and normalizing the fundus images, developed deep learning operational Artificial Intelligence (AI) network of feature extraction algorithm for detection of PDR on the fundus images and determined the output classification of the network encompassing the accuracy, sensitivity and specificity. …”
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Neurons to heartbeats: spiking neural networks for electrocardiogram pattern recognition by Wong, Yan Chiew, Mohamad Noor, Nor Amalia Dayana, Mohd Noh, Zarina, Sarban Singh, Ranjit Singh

“…Establishing functioning spiking neural networks (SNN) involves figuring out the neuron’s state through its activity level, challenging due to its resemblance to the human brain’s data processing, yet appealing due to factors like improved unsupervised learning methods, with ten parameters chosen for the learning algorithm of SNN. …”
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Oil palm maturity classifier using spectrometer and machine learning by Goh, Jia Quan

“…The prediction was able to produce 100% accuracies by using Linear and Weighted KNN as classification testing algorithm. …”
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Classification of transient disturbance using Wavelet based support vector machine / Fahteem Hamamy Anuwar by Anuwar, Fahteem Hamamy

“…Cross validation is used to find the best parameters related to kernels used followed by training and testing of the data sets. …”
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An enhanced gated recurrent unit with auto-encoder for solving text classification problems by Zulqarnain, Muhammad

“…However, GRU suffered from three major issues when it is applied for solving the text classification problems. The first drawback is the failure in data dimensionality reduction, which leads to low quality solution for the classification problems. …”
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Benthic habitat mapping and coral bleaching detection using quickbird imagery and Kd algorithm by Kabiri, Keivan

“…On the other hand, diffuse attenuation coefficient (kd) is another critical parameter for benthic habitat mapping using remotely sensed data. …”
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Hybrid ACO and SVM algorithm for pattern classification by Alwan, Hiba Basim

“…This study presents four algorithms for tuning the SVM parameters and selecting feature subset which improved SVM classification accuracy with smaller size of feature subset. …”
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Detection of Denial of Service Attacks against Domain Name System Using Neural Networks by Rastegari, Samaneh

“…These parameters are the inputs of the detector engine. In the current research for our machine learning engine, we aimed to find the optimum machine learning algorithm to be used as an IDS. …”
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Machine-learning-based adaptive distance protection relay to eliminate zone-3 protection under-reach problem on statcom-compensated transmission lines by Aker, Elhadi Emhemed Alhaaj Ammar

“…This current study proposes an intelligent data mining approach for the Machine Learning- Adaptive Distance Relay (ML-ADR) fault classification model using novel extracted 1-cycle transient voltage and current signals hidden knowledge from both healthy and faulty lines parameters. …”
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Intelligent classification algorithms in enhancing the performance of support vector machine by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Common methods associated in tuning SVM parameters will discretize the continuous value of these parameters which will result in low classification performance. …”
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Land use evaluation for Kuala Selangor, Malaysia using remote sensing and GIS technologies by Nedal A Mohammad, Sharifah Mastura SA , Johari Mat Akhir

“…In evaluating landuse for sustainable use of natural resources several maps were taken as parameters and obtained from digital classification of SPOT 2005 data by means of supervised modes with maximum likelihood algorithm using necessary ground truth data. …”
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Incremental continuous ant colony optimization for tuning support vector machine’s parameters by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Support Vector Machines are considered to be excellent patterns classification techniques. The process of classifying a pattern with high classification accuracy counts mainly on tuning Support Vector Machine parameters which are the generalization error parameter and the kernel function parameter.Tuning these parameters is a complex process and Ant Colony Optimization can be used to overcome the difficulty. …”
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Optimizing support vector machine parameters using continuous ant colony optimization by Alwan, Hiba Basim, Ku-Mahamud, Ku Ruhana

“…Hence, in applying Ant Colony Optimization for optimizing Support Vector Machine parameters, which are continuous parameters, there is a need to discretize the continuous value into a discrete value.This discretization process results in loss of some information and, hence, affects the classification accuracy and seek time.This study proposes an algorithm to optimize Support Vector Machine parameters using continuous Ant Colony Optimization without the need to discretize continuous values for Support Vector Machine parameters.Seven datasets from UCI were used to evaluate the performance of the proposed hybrid algorithm.The proposed algorithm demonstrates the credibility in terms of classification accuracy when compared to grid search techniques.Experimental results of the proposed algorithm also show promising performance in terms of computational speed.…”
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