Search Results - (( solution using bayesian algorithm ) OR ( java application customization algorithm ))

Experimental analysis on the anti spam effectiveness - commercial, Bayesian and Ngram algortihm / Ahmad Kamal Ramli by Ramli, Ahmad Kamal

“…By using standard series of text messages which consists of spam and ham words, N-Gram algorithm performed very well. …”
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Statistical approach on grading: mixture modeling by Md. Desa, Zairul Nor Deana

“…The Gibbs sampler algorithm is applied using the WinBUGS programming package. …”
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Identifying the Ideal Number Q-Components of the Bayesian Principal Component Analysis Model for Missing Daily Precipitation Data Treatment by Chuan, Zun Liang, Azlyna, Senawi, Wan Nur Syahidah, Wan Yusoff, Noriszura, Ismail, Tan, Lit Ken, Mu, Wen Chuan

“…In order to overcome this issue, this study desired to investigate the effectiveness of various Q-components of the Bayesian Principal Component Analysis model associates with Variational Bayes algorithm (BPCAQ-VB) in missing daily precipitation data treatment, which the ideal number of Q-components is identified by using The Technique for Order of Preference by Similarity to Ideal Solution (TOPSIS) algorithm. …”
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Model of Bayesian tangent eye shape for eye capture by Nsaef, Asama Kuder, Jaafar, Azizah, Sliman, Layth, Sulaiman, Riza, O. K. Rahmat, Rahmita Wirza

“…Obtaining a method in extracting quality of eye images automatically from the video stream is the main area of interest in this study. Besides, a Bayesian inference solution called Bayesian Tangent Eye Shape Model (BTESM) was suggested depending on estimation of tangent shape. …”
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A bayesian via laplace approximation on log-gamma model with censored data by Yusuf, Madaki Umar, Abu Bakar, Mohd Rizam, Husain, Qasim Nasir, Ibrahim, Noor Akma, Arasan, Jayanthi

“…Methods/Analysis: Alternatively, Bayesian estimation by MCMC simulation using the Random-walk Metropolis algorithm was applied, using AIC and BIC comparison makes it the smallest and great choice for fitting the survival models and simulations by Markov Chain Monte Carlo Methods. …”
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Statistical approach on grading the student achievement via mixture modelling by Md. Desa, Zairul Nor Deana, Mohamad, lsmail

“…The problem posterior density of the parameters which is analytically intractable. A solution using the Markov Chain Monte Carlo approach namely Gibbs sampler algorithm. …”
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Statistical approach on grading the student achievement via normal mixture modeling by Md. Desa, Zairul Nor Deana, Mohamad, Ismail, Mohd. Khalid, Zarina, Md. Zin, Hanafiah

“…The problem lies in estimating the posterior density of the parameters which is analytically intractable. A solution to this problem is using the Markov Chain Monte Carlo approach namely Gibbs sampler algorithm. …”
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An artificial immune system model as talent performance predictor / Siti ‘Aisyah Sa’dan, Hamidah Jantan and Mohd Hanapi Abdul Latif by Sa’dan, Siti ‘Aisyah, Jantan, Hamidah, Abdul Latif, Mohd Hanapi

“…Immune based algorithm is part of bio-inspired algorithms elicits theories which can act as an inspiration for computer-based solutions. …”
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BRAIN SOURCE LOCALIZATION TECHNIQUE FOR EEG SIGNALS BASED ON ENHANCED MULTIPLE SPARSE PRIORS by MUNSIF, ALI JATOI

“…It is an ill-posed problem in nature affected by uncertainty in solution. Different algorithms are proposed for the solution of this ill-posed problem which include minimum norm estimation (MNE), second order Laplacian based low resolution brain electromagnetic tomography (LORETA), standardized LORETA (sLORETA), exact LORETA, subspace based multiple signal classifier (MUSIC), Beamformer and Bayesian framework based multiple source priors (MSP). …”
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Variational Bayesian inference for exponentiated Weibull right censored survival data by Jibril Abubakar, Jibril Abubakar, Mohd Asrul Affendi Abdullah, Mohd Asrul Affendi Abdullah, Oyebayo Ridwan Olaniran, Oyebayo Ridwan Olaniran

“…The results from the experiments reveal that the Variational Bayesian (VB) approach is better than the competing Metropolis-Hasting Algorithm and the reference maximum likelihood estimates.…”
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Bayesian signaling game based efficient security model for MANETs by Olanrewaju, Rashidah Funke, Khan, Burhan Ul Islam, Anwar, Farhat, Mir, Roohie Naaz, Yaacob, Mashkuri, Mehraj, Tehseen

“…The regular nodes record incessantly to examine their corresponding nodes’ behaviours by using the belief system of Bayes-rules. On its comparison with existing schemes, it was revealed that the presented algorithm provides better identification of malicious nodes and attacks while delivering improved throughput and reduced false positive rate.…”
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Adaptive genetic algorithm to improve negotiation process by agents e-commerce by Ebadi, Sahar

“…The proposed negotiation algorithm employs Bayesian learning and similarity functions in order to predict opponent agent’s type and preferences. …”
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Pengesanan Kerosakan Bahan Penebat Transformer Dengan Menggunakan Rangkaian Neural Buatan by Che Osman, Suzita

“…Neural network can define the transformer fault through the learning process. Matlab7 is used to design the multilayer perceptron (MLP). Three types of learning algorithm are used in this project to train the MLP network, which are resilient backpropagation, Bayesian regularization and Levenberg-Marquardt. …”
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Reinforcement learning based techniques in uncertain environments: problems and solutions by AlDahoul, Nouar, Htike@Muhammad Yusof, Zaw Zaw, Akmeliawati, Rini, Shafie, Amir Akramin, Khan, Sheroz

“…It reviews problems of RL and solutions using different variants of RL namely: hierarchical RL, Bayesian model based learning, and Partially observable Markov decision processes (POMDP).…”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Alzaeemi, Shehab Abdulhabib, Tay, Kim Gaik, Huong, Audrey, Sathasivam, Saratha, Majahar Ali, Majid Khan

“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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A Recent Research on Malware Detection Using Machine Learning Algorithm: Current Challenges and Future Works by Gorment N.Z., Selamat A., Krejcar O.

Bayesian Framework based Brain Source Localization Using High SNR EEG Data by Jatoi, M.A., Kamel, N., Gaho, A.A., Dharejo, F.A.

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ECM-GT: design of efficient computational modelling based on game theoretical approach towards enhancing the security solutions in MANET by Khan, Burhan Ul Islam, Olanrewaju, Rashidah Funke, Anwar, Farhat, Mir, Roohie Naaz

“…The game model proposed also provides the finest actions of autonomous tactics for every node. A Bayesian-Equilibrium (BE) offers the best solution for games to resolve the incomplete information by joining strategies and players payoff which form an equilibrium. …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majahar Ali, Majid Khan

“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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Evolution Performance of Symbolic Radial Basis Function Neural Network by Using Evolutionary Algorithms by Shehab Abdulhabib Alzaeemi, Shehab Abdulhabib Alzaeemi, Kim Gaik Tay, Kim Gaik Tay, Audrey Huong, Audrey Huong, Saratha Sathasivam, Saratha Sathasivam, Majid Khan bin Majahar Ali, Majid Khan bin Majahar Ali

“…With the use of SRBFNN-2SAT, a training method based on these algorithms has been presented, then training has been compared among algorithms, which were applied in Microsoft Visual C++ software using multiple metrics of performance, including Mean Absolute Relative Error (MARE), Root Mean Square Error (RMSE), Mean Absolute Percentage Error (MAPE), Mean Bias Error (MBE), Systematic Error (SD), Schwarz Bayesian Criterion (SBC), and Central Process Unit time (CPU time). …”
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