Search Results - (( variable building model algorithm ) OR ( java application optimisation algorithm ))
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1
Study and Implementation of Data Mining in Urban Gardening
Published 2019“…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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2
SURE-Autometrics algorithm for model selection in multiple equations
Published 2016“…Meanwhile, practitioners who are usually non-experts and lack of statistical knowledge will face difficulties during the modelling process. Hence, algorithm with a step by step guidance is beneficial in model building, testing and selection. …”
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3
Price prediction model of green building based on machine learning algorithms / Nur Syafiqah Jamil
Published 2021“…Meanwhile, experiments using five common algorithms, Random Forest Regressor Model outperforms four (4) other algorithms in predicting the price of green building condominium, by training and validating the data-set using Split approach. …”
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4
Green building valuation based on machine learning algorithms / Thuraiya Mohd ... [et al.]
Published 2021“…To our knowledge, there is still no implementation of machine learning models on green building valuation features for building price prediction compared to conventional building development. …”
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Demand analysis of flood insurance by using logistic regression model and genetic algorithm
Published 2018“…The analysis was done by using logistic regression model, and to estimate model parameters, it is done with genetic algorithm. …”
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6
Development of a building energy analysis package (BEAP) and its application to the analysis of cool thermal energy storage systems
Published 2001“…Exact models for the proportional control of variable air volume and mix box air dampers are developed for variable air volume and dual-duct/multi-zone systems, respectively. …”
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7
Harmony Search algorithm-based gasoline consumption modeling for Indonesia
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Algorithmic approaches in model selection of the air passengers flows data
Published 2015“…Algorithm is an important element in any problem solving situation.In statistical modelling strategy, the algorithm provides a step by step process in model building, model testing, choosing the ‘best’ model and even forecasting using the chosen model.Tacit knowledge has contributed to the existence of a huge variability in manual modelling process especially between expert and non-expert modellers.Many algorithms (automated model selection) have been developed to bridge the gap either through single or multiple equation modelling.This study aims to evaluate the forecasting performances of several selected algorithms on air passengers flow data based on Root Mean Square Error (RMSE) and Geometric Root Mean Square Error (GRMSE).The findings show that multiple models selection performed well in one and two step-ahead forecast but was outperformed by single model in three step-ahead forecasts.…”
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9
General Algorithm of n-Multiple Coil Shape for Variable Links Hyper-Redundant Robotic Manipulator
Published 2011“…In this paper, a general algorithm for n-links hyper-redundant robot manipulator to produce n-multiple coil shape to reach final desired position with variable links is presented. …”
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Proceeding Paper -
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Penalized Quantile Regression Methods And Empirical Mode Decomposition For Improving The Accuracy Of The Model Selection
Published 2024“…Moreover, selecting the relevant variables when fitting the regression model is critical. …”
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11
Web-based expert system for material selection of natural fiber- reinforced polymer composites
Published 2015“…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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12
An Intelligent Process Model for Manufacturing System Optimization
Published 2012“…The model sets inventory target variable to be achieved with automated computation through the data input from users. …”
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Feasibility analysis for predicting the compressive and tensile strength of concrete using machine learning algorithms
Published 2024“…Also, the model performance was characterized based on the number of input variables utilized. …”
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Prediction of electronic cigarette and vape use among Malaysian: decision tree analysis
Published 2017“…The collected data was used to build and verified the model. Eight demographics variables (i.e., age, gender, race, religion, residence (urban/rural), marital, occupation and education) and twenty variables on perception of ECV were included as predictor variables. …”
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15
Building fuzzy variance gamma option pricing models with jump levy process
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Building fuzzy variance gamma option pricing models with jump levy process
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An artificial neural network approach in service life prediction of building components in Malaysia based on local environment and building service load
Published 2007“…The back-propagation learning algorithm is used as learning model. The environment load factors, workmanship, design, usage and level of maintenance are used as input variables in training process of the neural network model. …”
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Comparison between fuzzy bootstrap weighted multiple linear regression and multiple linear regression: a case study for oral cancer modelling
Published 2018“…Current technology advancement and increasing of development of the new or modified methodology building leads to the development of an alternative method for multiple linear regression model calculation. …”
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Automated calibration of baseline model for energy conservation using multi-objective Evolutionary Programming (EP) / Ahmad Amiruddin Mohammad Aris
Published 2019“…In this regard, three building parameters are taken as decision variables including occupancies, lightings and electrical equipment. …”
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20
Algorithm enhancement for host-based intrusion detection system using discriminant analysis
Published 2004“…Algorithms for building detection models are usually classified into two categories: misuse detection and anomaly detection. …”
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