Search Results - (( data evaluation _ algorithm ) OR ( variable estimation using algorithm ))

Electricity demand forecasting in Turkey and Indonesia using linear and nonlinear models based on real-value genetic algorithm and extended Nelder-Mead local search by Wahab, Musa

“…These problems resulted in estimation errors and high computational cost. Hybrid genetic algorithm (GA) and Nelder-Mead local search mode 1 has been used to minimize demand estimation errors. …”
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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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Extended multiple models selection algorithms based on iterative feasible generalized least squares (IFGLS) and expectation-maximization (EM) algorithm by Nur Azulia, Kamarudin

“…The empirical results for both algorithms performed well as compared to other models selection procedures, particularly using WQI data where the sample size is bigger and has good quality data. …”
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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.

“…Additionally, parametric and sensitivity analyses were used to assess the performance of the GPR and LR algorithms. …”

Hybrid optimization approach to estimate random demand by Wahab, Musa, Ku-Mahamud, Ku Ruhana, Yasin, Azman

“…The main objective of this study is to develop a demand forecasting model that should reflect the characteristics of random demand patterns.To accomplish this goal, a hybrid algorithm combining a genetic algorithm and a local search algorithm method was developed to overcome premature convergence in local optima problems.The performance of the hybrid algorithm was compared with a single algorithm model in estimating parameter values that minimize objective function which was used to measure the goodness-of-fit between the observed data and simulated results.However, two problems had to be overcome in the forecasting random demand model. …”
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Neighbour-based on-demand routing algorithms for mobile ad hoc networks by Ejmaa, Ali Mohamed E.

“…All the three proposed algorithms are evaluated using discrete event simulation, in particular Network Simulator tool (NS2), and compared with the latest routing algorithm (NCPR ) and fundamental algorithm (AODV) using five performance metrics. …”
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Slight-Delay Shaped Variable Bit Rate (SD-SVBR) Technique for Video Transmission by Ahmad Suki, Che Mohamed Arif

“…The new algorithm is capable of producing a high data rate and at the same time a better quantization parameter (QP) stability video sequence. …”
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Power System State Estimation In Large-Scale Networks by NURSYARIZAL MOHD NOR, NURSYARIZAL

“…The gain and the Jacobian matrices associated with the basic algorithm require large storage and have to be evaluated at every iteration, resulting in more computation time. …”
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Modelling monthly pan evaporation utilising Random Forest and deep learning algorithms by Abed M., Imteaz M.A., Ahmed A.N., Huang Y.F.

Comparison between Newton’s Method and a new Scaling Newton Method / Ramizah Baharuddin by Baharuddin, Ramizah

“…The third estimate is obtained by using the tangent line of f (x) at the second estimate. …”
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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.

Comparing three methods of handling multicollinearity using simulation approach by Adnan, Norliza

“…RR on the other hand is the modified least square method that allows a biased but more precise estimator. The algorithm is described and for the purpose of comparing the three methods, simulated data sets where the number of cases was less than the number of observations were used. …”
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Hybrid histogram and neural based call admission control for VBR video traffic. by Khalil, Ibrahim, Mohd Ali, Borhanuddin

“…In this paper, we have proposed a hybrid Neural Network (NN) approach to estimate cell loss rate of Variable Bit Rate (VBR) Video traffic for Call Admission Control (CAC) purpose in ATM environment Existing CAC algorithms, which are mostly based on on-off model, do not appear to apply well to VBR video traffic. …”
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Evaluation of tree growth characteristics of harum manis mango from multitemporal UAV image in plantation farm by Muhammad Yusuf, Akmal Alif

“…Furthermore, high-resolution spatial imagery generated by unmanned aerial vehicles (UAVs) can provide precise and effective estimate of tree measurements and structural canopy variables. …”
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A Comparative Study On Some Methods For Handling Multicollinearity Problems by Adnan, Norliza, Ahmad, Maizah Hura, Adnan, Robiah

“…RR on the other hand is the modified least square method that allows a biased but more precise estimator. The algorithm is described and for the purpose of comparing the three methods, simulated data sets where the number of cases were less than the number of observations used. …”
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A comparative study on some methods for handling multicollinearity problems by Adnan, Norliza, Ahmad, Maizah Hura, Adnan, Robiah

“…RR on the other hand is the modified least square method that allows a biased but more precise estimator. The algorithm is described and for the purpose of comparing the three methods, simulated data sets where the number of cases were less than the number of observations used. …”
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Properties of selected garma models and their estimation procedures by Ramiah Pillai, Thulasyammal

“…The focus of this study is to investigate the properties specically the variance and autocovariance of the GARMA (p; q; ±1; ±2) models. We also study the estimation of the parameters of these models. Evaluation of the performance of two estimators based on the Hannan-Rissanen Algorithm Estimator (HRA) and the Whittle's Estimator (WE) through a series of simulation studies have been conducted in this thesis. …”
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Robust Data Fusion Techniques Integrated Machine Learning Models For Estimating Reference Evapotranspiration by Chia, Min Yan

“…The accuracy of the estimations using the MLP, SVM and ANFIS could be improved by the inclusion of different complementary variables, which vary depending on the geographical characteristics at the meteorological stations. …”
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Maximum 2-satisfiability in radial basis function neural network by Shehab Abdulhabib Alzaeemi, Saratha Sathasivam, Mohd Shareduwan Mohd Kasihmuddin, Mohd. Asyraf Mansor

“…We utilize Dev C++ as the platform of training and testing our proposed algorithm. In this study, the effectiveness of RBFNN-MAX2SAT can be estimated by evaluating the proposed models with testing data sets. …”
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"Application of Neural Network in developing Virtual Analyzer of Reformate Research Octane Number" by Suharin, Zuraihan Selina

“…For this case study, Backpropagation Network and Levenberg Algorithm are used. To evaluate the performance of the neural network model, the trained network was simulated using data that the network has not been trained before. …”
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