Waste management, quality of life and natural resources utilization matter for renewable electricity generation: The main and moderate role of environmental policy

Utilities Policy, Journal Year: 2023, Volume and Issue: 82, P. 101584 - 101584

Published: June 1, 2023

Language: Английский

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Comparative techno-economic analyses and optimization of standalone and grid-tied renewable energy systems for South Asia and Sub-Saharan Africa

Results in Engineering, Journal Year: 2024, Volume and Issue: 21, P. 101964 - 101964

Published: March 1, 2024

This study evaluates the economic, technical, and environmental performance of stand-alone grid-tied HRES in Khiriya Bharka, India; Thayet Township, Myanmar; Lower Manya Krobo, Ghana; Mamfe, Cameroon, considering different regional solar radiation, wind speed diversity, climate. The are designed modeled using Hybrid Optimization Multiple Energy Resources software (HOMER PRO) to meet consumers' daily loads selected places. analysis results compared levelized cost energy (LCOE), net present (NPC), greenhouse gas (GHG) emission, renewable fraction (RF), optimum system configuration. optimal configurations combination PV-WT-DG-BAT-CON for India, Ghana, respectively, best configuration Myanmar, is WT-DG-BAT-CON. LCOE considered places without grid connection $0.127/kWh, $0.145/kWh, $0.174/kWh, $0.143/kWh, respectively. 0.026$/kWh, 0.0286$/kWh, 0.01$/kWh, 0.0281$/kWh research can be useful planning between Asia African countries by comparing determine finding optimization under climate conditions. These further validated loss power supply probability (LPSP) particle swarm (PSO). To better inform policymakers stakeholders various regions, this aims assess compare solutions terms their feasibility, cost-effectiveness, impact, sustainability across a range geographical, social, economic contexts.

Language: Английский

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An automatic teeth arrangement method based on an intelligent optimization algorithm and the Frenet–Serret formula

Biomedical Signal Processing and Control, Journal Year: 2025, Volume and Issue: 105, P. 107606 - 107606

Published: Feb. 5, 2025

Language: Английский

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Investigating the intensity of GHG emissions from electricity production in Iran using renewable sources

Results in Engineering, Journal Year: 2022, Volume and Issue: 17, P. 100819 - 100819

Published: Dec. 6, 2022

The emission intensity is considered important data in determining technical and environmental efficiency power plants. In this research, the goal to determine of greenhouse gas emissions electricity production sector Iran under influence new energies. To achieve goal, total gases produced a year fossil renewable plants are divided by obtained quantitatively terms tCO2/kWh. Also, effect each primary source generation analyzed separately intensity. results showed that participation sources highest situation was about 9.5%, their 2.2 fuel-based plant had an estimated 506 tCO2/kWh same year. Although policies seek reduce emissions, generally, growth index negative, there many fluctuations process. With reduction rainfall water behind dams, dependence on has decreased significantly So when precipitation significant, increased from its minimum value 613.6 654.34 low rainfall. As result, it been suggested potential solar resources, which lower than other one most reliable stable sources, should be used more effectively sector.

Language: Английский

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Codon-mRNA prediction using deep optimal neurocomputing technique (DLSTM-DSN-WOA) and multivariate analysis

Results in Engineering, Journal Year: 2022, Volume and Issue: 17, P. 100847 - 100847

Published: Dec. 20, 2022

Based on the principle that upgrading of any nation begins by raising level performance its institutions serve community, including Ministry Healthcare and given development in field technology, growing need to save life persons from different types diseuses determined proteins increase or prevent diseuses, so it is found world has tended recent years intelligent data analysis techniques spatially deep neurocomputing healthcare fields predict high quality results short time. The paper presents model Codon-mRNA Prediction using Deep Optimal Neurocomputing Technique (DLSTM-DSN-WOA) Multivariate Analysis. That consists five basic stages: first stage process collecting preparing make suitable form for decision-making included several steps, processing missing values condign target, second involved develop optimization algorithms called Whale Optimization Algorithm (WOA) build optimal structure one network (i.e., long short-term memory (LSTM)). tool select after achieve include PSO, BOA, WOA, COA, FA; this focus points: main programming parameters, advantages, disadvantages each algorithm. . WOA used find best technique LSTM choose campier among multi Recurrent Neural Network (RNN), Gated Unit (GRU), Long Short-Term Memory (LSTM), Bi-Directional (BiLSTM), AlexNet, GoogleNet). perform based programing steps parameters affect algorithm, because as algorithm having many advantages characteristics. proposed appears pragmatic reduce computation time handle huge real data.

Language: Английский

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Efficient city supply chain management through spherical fuzzy dynamic multistage decision analysis

Engineering Applications of Artificial Intelligence, Journal Year: 2023, Volume and Issue: 126, P. 106712 - 106712

Published: July 27, 2023

Language: Английский

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Predicting Day-Ahead Electricity Market Prices through the Integration of Macroeconomic Factors and Machine Learning Techniques

International Journal of Computational Intelligence Systems, Journal Year: 2024, Volume and Issue: 17(1)

Published: Jan. 15, 2024

Abstract Several events in the last years changed to some extent common understanding of electricity day-ahead market (DAM). The shape price curve has been altered as factors that underpinned forecast (EPF) lost their importance and new influential emerged. In this paper, we aim showcase changes EPF, understand effects uncertainties propose a forecasting method using machine learning (ML) algorithms cope with random such COVID-19 pandemic conflict Black Sea region. By adjusting training period according standard deviation reflects volatility, feature engineering by two regressors for weighing results, significant improvements performance EPF are achieved. One contributions proposed consists considering variation. Thus, introduce rule-based approach given an empirical observation days higher growth prices interval should be shortened, capturing sharp variations prices. results several cutting-edge ML represent input predictive meta-model obtain best solution. dataset spans from Jan. 2019 Aug. 2022, testing both stable more tumultuous intervals proving its robustness. This analysis provides decision makers trends suggests measures combat spikes. Numerical findings indicate on average mean absolute error (MAE) improved 48% root squared (RMSE) 44% compared baseline model (without engineering/adjusting training). When output is weighted meta-model, MAE further 2.3% 2020 5.14% 2022. Less errors recorded like (MAE = 6.71, RMSE 14.67) 2021 2022 9.45, 20.64).

Language: Английский

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Analysis of correlation between climate change and energy poverty: A panel data analysis

Energy, Journal Year: 2025, Volume and Issue: unknown, P. 135247 - 135247

Published: March 1, 2025

Language: Английский

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Incomplete multi-view clustering by simultaneously learning robust representations and optimal graph structures

Information Sciences, Journal Year: 2023, Volume and Issue: 640, P. 119038 - 119038

Published: May 3, 2023

Language: Английский

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Investigating the impact of data heterogeneity on the performance of federated learning algorithm using medical imaging

PLoS ONE, Journal Year: 2024, Volume and Issue: 19(5), P. e0302539 - e0302539

Published: May 15, 2024

In recent years, Federated Learning (FL) has gained traction as a privacy-centric approach in medical imaging. This study explores the challenges posed by data heterogeneity on FL algorithms, using COVIDx CXR-3 dataset case study. We contrast performance of Averaging (FedAvg) algorithm non-identically and independently distributed (non-IID) against identically (IID) data. Our findings reveal notable decline with increased heterogeneity, emphasizing need for innovative strategies to enhance diverse environments. research contributes practical implementation FL, extending beyond theoretical concepts addressing nuances imaging applications. uncovers inherent due diversity. It sets stage future advancements effectively manage especially sensitive fields like healthcare.

Language: Английский

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