Search Results - (( java application optimisation algorithm ) OR ( carlo simulation learning algorithm ))

A modified weight optimisation for higher-order neural network in time series prediction by Husaini, Noor Aida

“…The performance of MCS-MCMC learning algorithm was validated with several test functions and compared with those of MCS learning algorithm. …”
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Adsorption of non-ionic surfactants on organoclays in drilling fluid investigated by molecular descriptors and Monte Carlo random walk simulations by Kania, Dina, Yunus, Robiah, Omar, Rozita, Abdul Rashid, Suraya, Mohamed Jan, Badrul, Aulia, Akmal

“…Here, the fundamental phenomena involved in non-ionic surfactant adsorption on organoclays and how it affects the rheology of synthetic-based drilling fluids were elucidated by the analysis of molecular descriptors and Monte Carlo simulations. Using the Random Forests machine learning algorithm software, the non-ionic surfactant adsorption on organoclays was found to be affected mainly by the hydrophobicity and molecular shape of hydrophobic chains of non-ionic surfactants. …”
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Study and Implementation of Data Mining in Urban Gardening by Mohana, Muniandy, Lee, Eu Vern

“…The system is essentially a three-part development, utilising Android, Java Servlets, and Arduino platforms to create an optimised and automated urban-gardening system. …”
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Machine learning predictions of stock market pattern using Econophysics approach by Roslan, Nur Nadia Hani, Abdullah, Shahino Mah

“…There are various techniques for identifying and observing the stock market patterns, one of the techniques is to use Python programming to evaluate and possibly forecast stock market behaviour through predictive modelling, combining both machine learning and Econophysics insights. Hence, this research will be using Monte Carlo Simulation and identify which machine learning algorithm is suitable for predicting stock market patterns. …”
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Physics-guided deep neural network to characterize non-Newtonian fluid flow for optimal use of energy resources by Kumar, A., Ridha, S., Narahari, M., Ilyas, S.U.

“…The detailed parametric analysis exhibits the competency of the proposed algorithm to explain the rheological features. Monte-Carlo simulation is performed by propagating uncertainty to investigate the dominant parameters affecting simulated results. …”
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An augmented sequential MCMC procedure for particle based learning in dynamical systems by Javvad ur Rehman, M., Dass, S.C., Asirvadam, V.S.

“…An augmented sequential Markov Chain Monte Carlo (ASMCMC) algorithm is developed for obtaining the posterior distribution of unknown parameters. …”
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Estimation of Information Measures for Power-Function Distribution in Presence of Outliers and Their Applications by Hassan, Amal Soliman, Elsherpieny, Elsayed Ahmed, Mohamed, Rokaya Elmorsy

“…The Bayesian estimators were computed empirically using a Monte Carlo simulation based on the Gibbs sampling algorithm. …”
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Development Of Construction Noise Prediction Method Using Deep Learning Model by Siew, Jun Teng

“…A simple prediction chart method was developed on top of a stochastic algorithm called Monte Carlo simulation by complying with the standard BS 5228 for the noise prediction in the environmental impact assessment during the planning stage of a construction project. …”
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Web-based expert system for material selection of natural fiber- reinforced polymer composites by Ahmed Ali, Basheer Ahmed

“…Finally, the developed expert system was deployed over the internet with central interactive interface from the server as a web-based application. As Java is platform independent and easy to be deployed in web based application and accessible through the World Wide Web (www), this expert system can be one stop application for materials selection.…”
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Determining malaria risk factors in Abuja, Nigeria using various statistical approaches by Segun, Oguntade Emmanuel

“…Data collected were used for the multilevel analysis, Markov Chain Monte Carlo (MCMC) simulation via WinBUGS algorithm and influence diagrams for BBNs. …”
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Development of a multi criteria decision support system using convolutional neural network and jaya algorithm for water resources management / Chong Kai Lun by Chong , Kai Lun

“…Besides, the Monte-Carlo simulations demonstrated that all the values lie within the 95% confidence level. …”
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End-to-end DVB-S2X system design with deep learning-based channel estimation over satellite fading channels by Mfarej, Sumaya Dhari Awad

“…In the fourth part a deep learning (DL) algorithm of channel estimation for two fad�ing channel models, Tropical and Temperate in the satellite communication system is presented. …”
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Configurations of memristor-based APUF for improved performance by Teo J.H.L., Hashim N.A.N., Ghazali A., Hamid F.A.

“…Its advantage is in its challenge-dependent delays, which cannot be modeled by machine learning algorithms. In this paper, further improvement is proposed, which are circuit configurations to the memristor-based APUF. …”

Multi depot dynamic vehicle routing problem with stochastic road capacity for emergency medical supply delivery in humanitarian logistics by Anuar, Wadi Khalid

“…The contributions of the research are as follows: (1) The MDP model for MDDVRPSRC, deterministic D-MDVRPRC as well as 2 stage stochastic ILP MDVRPSRC-2S models are respectively developed and presented; (2) based on the MDVRPSRC- 2S it is shown how 2-stage stochastic programming model can be applied through CPLEX execution during each of Monte Carlo simulated PDS - RA by proposing another two models as two reduced version (MDVRPSRC-2S1 and MDVRPSRC- 2S2) of the MDVRPSRC-2S; (3) the radial tremor disaster dispersion from a single or multiple epicentres and the corresponding deterioration of road capacity distribution mean and travel time are proposed; (4) the solution algorithm: TBIH-1, and it’s 4 variants (TBIH-2, TBIH-3, TBIH-4 and TBIH-5) are presented; (5) test dataset is developed consists of simulated road networks and the damage unit of each roads due to the earthquake for experimentation and simulation purposes, and finally (6) a decision support system (MDDVRPSRC DSS) for simulating online delivery operation during disaster is designed. …”
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