Search Results - (( variable respective models algorithm ) OR ( java application optimisation algorithm ))

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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Independent And Dependent Job Scheduling Algorithms Based On Weighting Model For Grid Environment by M. Al-Najjar, Hazem

“…The resulting model is then applied onto the independent and dependent job scheduling algorithms to verify the capability of proposed job scheduling model in a real environment. …”
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Predicting crop yield and field energy output for oil palm using genetic algorithm and neural network models by Hilal, Yousif Yakoub

“…The GA-ANN and GA-NARX models perform markedly better than the other models in the most training algorithms with different numbers of hidden layers.…”
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Development of genetic algorithm for optimization of yield models in oil palm production by Hilal, Yousif Y., Wan Ismail, Wan Ishak, Yahya, Azmi, Ash’aari, Zulfa Hanan

“…Moreover, models were built on the basis of variables that have been selected by the GA. …”
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Characteristic wavelength optimization for partial least squares regression using improved flower pollination algorithm by Pauline Ong, Pauline Ong, Jinbao Jian, Jinbao Jian, Jianghua Yin, Jianghua Yin, Guodong Ma, Guodong Ma

“…First, the flower pollination algorithm is applied to search for informative spectral variables, followed by variable elimination. …”
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Harmony Search algorithm-based gasoline consumption modeling for Indonesia by Anggarani, Riesta, Watada, Junzo

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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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Predicting evaporation with optimized artificial neural network using multi-objective salp swarm algorithm by Ehteram M., Panahi F., Ahmed A.N., Huang Y.F., Kumar P., Elshafie A.

Widely linear dynamic quaternion valued least mean square algorithm for linear filtering by Mohammed, Aldulaimi Haydar Imad

“…A superior performance is achieved by the proposed algorithms in system modeling where the DQLMS was able to track the correct weights values of the different modeled systems 430 sample faster than the QLMS and ZA-QLMS algorithms while the WL-DQLMS was faster than the WLQLMS algorithm by 950 samples. …”
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Modelling of river flow using particle swarm optimized cascade-forward neural networks: A case study of kelantan river in malaysia by Hayder G., Solihin M.I., Mustafa H.M.

“…0.662 for weighted rainfall, evaporation, and temperature, respectively. Additionally, the developed nonlinear multivariable regression model using CFNNPSO produced acceptable prediction accuracy during model testing with the regression coefficient (R2), root mean square error (RMSE), and mean of percentage error (MPE) of 0.88, 191.1 cms and 0.09%, respectively. …”

Evaluating enhanced predictive modeling of foam concrete compressive strength using artificial intelligence algorithms by Abdellatief M., Wong L.S., Din N.M., Mo K.H., Ahmed A.N., El-Shafie A.

“…Therefore, it is recommended to utilize the prediction algorithms within the range of input variables employed in this investigation for optimal results. ? …”

The Integration of Nature-Inspired Algorithms with Least Square Support Vector Regression Models: Application to Modeling River Dissolved Oxygen Concentration by Yaseen, Zaher, Ehteram, Mohammad, Sharafati, Ahmad, Shahid, Shamsuddin, Al-Ansari, Nadhir, El-Shafie, Ahmed

“…The accuracy of the LSSVM-BA model compared with those of the M5 Tree and MARS models is found to increase by 20% and 42%, respectively, in terms of the root-mean-square error. …”
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Model selection approaches of water quality index data by Kamarudin, Nur Azulia, Ismail, Suzilah

“…Automatic model selection by using algorithm can avoid huge variability in model specification process compared to manual selection.With the employment of algorithm, the right model selected is then also used for forecasting purposes. …”
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Feature selection and optimal neural network algorithm for the state of charge estimation of lithium-ion battery for electric vehicle application by Hossain Lipu M.S., Hannan M.A., Hussain A.

Robust Estimation Methods And Outlier Detection In Mediation Models by Fitrianto, Anwar

“…Mediation models refer to the relationships among three variables: an independent variables (IV), a potential mediating variable (M), and a dependent variable (DV). …”
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Feasibility analysis for predicting the compressive and tensile strength of concrete using machine learning algorithms by Ziyad Sami B.H., Ziyad Sami B.F., Kumar P., Ahmed A.N., Amieghemen G.E., Sherif M.M., El-Shafie A.

“…Also, the model performance was characterized based on the number of input variables utilized. …”

Rainfall prediction using multiple inclusive models and large climate indices by Mohamadi S., Sheikh Khozani Z., Ehteram M., Ahmed A.N., El-Shafie A.

Modelling and analysis of sensor fault tolerant control using behavioral approach to systems theory by Ng, Peng Hong

“…Fault related parameters thus can be considered as subsets of the abovementioned trajectories and therefore can be modelled and analysed. Mathematical models of the plants are first derived through the description of the manifest behavior by elimination of the latent variables via a systematic algorithm. …”
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Predicting sea levels using ML algorithms in selected locations along coastal Malaysia by Hazrin N.A, Chong K.L, Huang Y.F, Ahmed A.N, Ng J.L, Koo C.H, Tan K.W, Sherif M, El-shafie A

“…Notably, lag variables with less than a 7-day lag could degrade the model's accuracy in representing ground reality. …”

Analysis and Optimization of Ultrasound-Assisted Alkaline Palm Oil Transesterification by RSM and ANN-GA by Sajjadi, B., Davoody, M., Abdul Raman, Abdul Aziz, Ibrahim, Shaliza

“…The maximum reaction yields of 95.2% and 95.1% were predicted by the RSM and ANN-GA models, respectively, at the optimum conditions. The conditions predicted by RSM and ANN-GA proved to be feasible for modeling and optimizing transesterfication yield with an accuracy of 99.18% and 99.14% and biodiesel properties of 98.61% and 98.28%, respectively.…”
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