Search Results - (( solution construction waste algorithm ) OR ( variable estimation learning algorithm ))

Assessment of forest aboveground biomass estimation from superview-1 satellite image using machine learning approaches / Azinuddin Mohd Asri by Mohd Asri, Azinuddin

“…The suitable independent variables (hL, DBH, and CPA) were vital to estimating the dependent variable (Sc) and producing a carbon stock map for the final result. …”
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A greedy heuristics multiple criteria model for solving multi-landfill site selection and plant propagation algorithm for improving waste collection vehicle routing solutions by Nur Azriati, Mat

“…Then, a multiple criteria greedy heuristic model was proposed to construct WCVRP solutions and to find a new landfill site(s) with the minimum total operational costs. …”
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Enhanced Heuristic Algorithms with A Vehicle Travel Speed Model for Time-Dependent Vehicle Routing: A Waste Collection Problem by Mat, Nur Azriati, Benjamin, Aida Mauziah, Abdul-Rahman, Syariza

“…However, in this paper the static speed that was considered in both algorithms were improved by introducing dynamic travel speeds to construct vehicle routes for the waste collection drivers. …”
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Enhanced heuristic algorithms with a vehicle travel speed model for time-dependent vehcile routing: A waste collection problem by Mat, Nur Azriati, Benjamin, Aida Mauziah, Abdul-Rahman, Syariza

“…This paper proposes a vehicle travel speed model to enhance two heuristic algoritihms from previous studies, namely current initial solution (CIS) and different initial customer (DIC).Both algorithms are used to solve a real-life waste collection vehicle routing benchmark problem with dynamic travel speeds. …”
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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.

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Nearest greedy for solving the waste collection vehicle routing problem: A case study by Mat, Nur Azriati, Benjamin, Aida Mauziah, Abdul-Rahman, Syariza, Wibowo, Antoni

“…This paper presents a real case study pertaining to an issue related to waste collection in the northern part of Malaysia by using a constructive heuristic algorithm known as the Nearest Greedy (NG) technique. …”
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SLIDING WINDOW TRAINING ALGORITHMS USING MLP-NETWORK FOR CORRELATED AND LOST PACKET DATA by AHMED IZZELDIN, HUZAIFA TAWFEIG

“…This thesis gives a systematic investigation of various MLP learning mainly Sliding Window (SW) learning mode which is treated as the adaptation of offline algorithms into online application Consequently this thesis reviews various offline algorithms including: batch backpropagation, nonlinear conjugate gradient, limited memory and full-memory Broyden, Fletcher, Goldfarb and Shanno algorithms and different forms of the latest proposed bimary ensemble learning. …”
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Improving forest above-ground biomass estimation by integrating individual machine learning models by Luo, Mi, Ahmad Anees, Shoaib, Huang, Qiuyan, Qin, Xin, Qin, Zhihao, Fan, Jianlong, Han, Guangping, Zhang, Liguo, Mohd Shafri, Helmi Zulhaidi

“…Machine learning algorithms have been proven to have great potential in forest AGB estimation with remote sensing data. …”
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An improved partial comparison optimization for utilizing landfill facilities in a waste collection vehicle routing problem by Fazlini, Hashim

“…The improved PCO incorporates a Nearest Greedy (NG) algorithm for initial solution construction, dynamic parameter adjustment, and two additional neighborhood operators. …”
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Dynamic Bayesian Networks and Variable Length Genetic Algorithm for Dialogue Act Recognition by Ali Yahya, Anwar

“…In the selection phase, a new variable length genetic algorithm is applied to select the lexical cues. …”
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Robust Data Fusion Techniques Integrated Machine Learning Models For Estimating Reference Evapotranspiration by Chia, Min Yan

“…Observations of the results of this study revealed that the solar radiation (Rs) is the most essential variable for estimating ET0 in Peninsular Malaysia. …”
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A case study on quality of sleep and health using Bayesian networks by Hong , Choon Ong, Chiew , Seng Lee, Chye , Ching Sia

“…The network scores computation is implemented to estimate the fitting of the resulting network of each structural learning algorithm in order to choose the best-fitted network. …”
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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.

Long-term electrical energy consumption: Formulating and forecasting via optimized gene expression programming / Seyed Hamidreza Aghay Kaboli by Seyed Hamidreza , Aghay Kaboli

“…In the developed feature selection approach, multi-objective binary-valued backtracking search algorithm (MOBBSA) is used as an efficient evolutionary search algorithm to search within different combinations of input variables and selects the non-dominated feature subsets, which minimize simultaneously both the estimation error and the number of features. …”
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Enhanced Adaptive Confidence-Based Q Routing Algorithms For Network Traffic by Yap, Soon Teck

“…The ECDRQ Routing Algorithm integrates the ECQ and Dual Reinforcement Q (DRQ) Routing Algorithms with Alternative Q Value Approach to minimise the effect of partially learning cycle. …”
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Applying machine learning and particle swarm optimization for predictive modeling and cost optimization in construction project management by almahameed, Bader aldeen, Bisharah, Majdi

“…Particle Swarm Optimization (PSO) has demonstrated its efficacy in addressing the issue of construction waste reduction and enhancing the accuracy of cost estimation through the identification of optimal combinations of variables. …”
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Creating Air Temperature Models for High-Elevation Desert Areas Using Machine Learning by Forooshani, Massoud, Gegov, Alexander, Pepin, Nick, Adda, Mo

“…This is particularly important in high-elevation regions. In this study, we estimate Ta in the high-elevation desert zone of Kilimanjaro (>4500m) using four models (five models including the benchmark model) with unique sets of inputs using five machine learning (ML) algorithms. …”
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An improved machine learning model of massive Floating Car Data (FCD) based on Fuzzy-MDL and LSTM-C for traffic speed estimation and prediction by Ahanin, Fatemeh

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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.

A decomposed streamflow non-gradientbased artificial intelligence forecasting algorithm with factoring in aleatoric and epistemic variables / Wei Yaxing by Wei , Yaxing

“…Finally, one key drawback of estimating streamflow outlined above is that it does not account for variability. …”
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