Search Results - (( model validation window algorithm ) OR ( whale optimization means algorithm ))

WHALE OPTIMIZATION NEURAL NETWORK FOR DAILY WATER LEVEL FORECASTING CONSIDERING THE CHANGING CLIMATE by Kuok, King Kuok, Chiu, Po Chan, Md. Rezaur, Rahman, Teng, Yeow Haur

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Investigating dam reservoir operation optimization using metaheuristic algorithms by Lai V., Essam Y., Huang Y.F., Ahmed A.N., El-Shafie A.

Enhancement of Groundwater-Level Prediction Using an Integrated Machine Learning Model Optimized by Whale Algorithm by Banadkooki F.B., Ehteram M., Ahmed A.N., Teo F.Y., Fai C.M., Afan H.A., Sapitang M., El-Shafie A.

“…For the test stage, the mean absolute error of the MLP�WA model decreased to 30% and from 31 to 38% as compared to the radial basis function�whale algorithm (RBF�WA) and GP models, respectively. …”

Application and evaluation of the evolutionary algorithms combined with conventional neural network to determine the building energy consumption of the residential sector by Wang G., Mukhtar A., Moayedi H., Khalilpoor N., Tt Q.

“…The primary objectives were to assess the performance of three evolutionary algorithms ? Heap-Based Optimizer (HBO), Multiverse Optimizer (MVO), and Whale Optimization Algorithm (WOA) ? …”

Hybrid flow shop scheduling with energy consumption in machine shop using moth flame optimization by M. F. F., Ab Rashid, Ahmad Nasser, Mohd Rose, N. M. Zuki, N. M.

“…The results were also compared with relatively recent algorithm such as Whale Optimization Algorithm and Harris Haws Optimization. …”
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An enhancement of sliding window algorithm for rainfall forecasting by Azahar, Siti Nor Fathihah, Othman, Mahmod, Saian, Rizauddin

“…The validation analysis shows that the proposed method has a higher forecasting accuracy than the previous method of sliding window algorithm.…”
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Mathematical models and optimization algorithms for low-carbon Location-Inventory-Routing Problem with uncertainty by Liu, Lihua

“…This thesis also aims to solve the low-carbon LIRP model with uncertainty factors such as carbon trading, customer demand, shortages, and soft time windows using advanced algorithms. …”
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Fuzzy time series sliding window model for rainfall forecasting / Siti Nor Fathihah Azahari by Azahari, Siti Nor Fathihah

“…The chosen division groups of u,, is applied in FTSSW model. At the same time, FTS is combined with Sliding Window Algorithm (SWA) to enhance the model. …”
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Multi-criteria optimization framework for cloudlet computing in WMANs: integrating VL-WIDE and AHP for enhanced decision-making by Muwafaq, Layth, Noordin, Nor K, Othman, Mohamed, Ismail, Alyani, Hashim, Fazirulhisyam

“…Our method employs a variable-length multi-objective whale optimization integrated with differential evolution (VL-WIDE) to tackle the optimization problem, dynamically adjusting to the WMAN environment while optimizing delay, energy consumption (both user device and cloudlet), and cloudlet deployment cost. …”
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Formulating and solving stochastic truck and trailer routing problems using meta-heuristic algorithms / Seyedmehdi Mirmohammadsadeghi by Seyedmehdi, Mirmohammadsadeghi

“…Therefore, truck and trailer routing problem with stochastic demands and time window (TTRPSDTW) is more realistic and thus modeled. …”
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Predictive dynamic CFD approach to reducing airborne transmission in naturally ventilated hospital rooms: Impact of window opening angles during transitional cold seasons in China... by Haowei , Yu

“…Stepwise polynomial regression has been validated as a novel algorithm that can effectively predict window opening angles. …”
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Memetic Heuristic Approach for Solving Truck and Trailer Routing Problems with Stochastic Demands and Time Windows by Mirmohammadsadeghi, S., Ahmed, S.

“…The purpose of this study is to expand the deterministic TTRP model by introducing stochastic demand and time window constraints to bring the TTRP model closer to reality and solve the model in a reasonable timeframe by administering the memetic algorithm (MA). …”
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Revitalizing old drugs: uncovering potential dengue antivirals through in silico target prediction and in vitro validation / Zafirah Liyana Abdullah by Abdullah, Zafirah Liyana

“…For the L-B approach, a Random Forest (RF) one-vs-one classification model was utilized while the PCM model employed the Parzen-Rosenblatt Windows (PRW) algorithm. …”
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MUD-WEIGHT PREDICTION FOR DEVIATED DRILLING by Yusoff, Muhamad Zakwan

“…The fourth phase was testing and validation of the model and also improving the user interface. …”
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DRIFT ANALYSIS ON NEURAL NETWORK MODEL OF HEAT EXCHANGER FOULING by M., Ramasamy, A., Shahid, H., Zabiri

“…Due to the empirical nature of NN, it is typically valid only for small operating windows. As the process drifts, the prediction accuracy of such models deteriorates very much rendering the models unfit. …”
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Type 2 Fuzzy Inference-Based Time Series Model by Nur Fazliana, Rahim, Mahmod, Othman, Rajalingam, Sokkalingam, Evizal, Abdul Kadir

“…In this research, the data sets from previous studies of crude palm oil prices were used to further analyze and validate the proposed model. With suitable class intervals and fuzzy rules generated, the forecasting values obtained were more precise and closer to the actual values. …”
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Developing individualised therapy for colistin through application of pharmacokinetic model tailored for critically ill Malaysian patients utilizing the HPLC-FLD by Zabidi, Mohd Shafie

“…The Non-Parametric Adaptive Grid algorithm within Pmetrics software was used to develop a colistin pharmacokinetic model using meta-analysis data from 15 pharmacokinetic studies, and external validation of the final model was performed in 25 subjects (Malaysian and meta-analysis data). …”
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Optimization of Microbial Electrolysis Cell for Sago Mill Wastewater Derived Biohydrogen via Modeling and Artificial Neural Network by Mohamad Afiq, Mohd Asrul

“…The model reliability describes the second sub-objective, which is to determine the feasible operating window of the MEC using multiple-objective optimization based on the nonlinear convex method using gradient descent algorithm as the objective function in maximizing the percentage efficiency of the MEC after validating the mathematical model. …”
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Numerical Modelling of the Electric Vehicle Cabin Cooling by Jong, Fabian Chin Peng

“…The model is validated for accuracy and it is found to have an average relative error of 15.11 %. …”
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Radar - Acoustic Vehicle Classification System based on shallow Convolutional Neural Network by Yasmin, Aida

“…The objectives of this research are threefold: (i) to develop a dual-channel VC framework using radar and acoustic modalities, (ii) to design a dual-channel shallow CNN for efficient vehicle classification, and (iii) to validate the model using real-world traffic data. Experimental evaluation explored variations in time window lengths, spectrogram sizes, fusion stages, and operators. …”
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