Artificial Neural Network Model to Predict the Exportation of Traditional Products of Colombia DOI Creative Commons

Andrea C. Gómez,

Lilian A. Bejarano, Helbert Espitia

et al.

Computation, Journal Year: 2024, Volume and Issue: 12(11), P. 221 - 221

Published: Nov. 4, 2024

This article develops the design, training, and validation of a computational model to predict exportation traditional Colombian products using artificial neural networks. work aims obtain single multilayer network. The number historical input data (delays), layers, neurons were considered for network design. In this way, an experimental design 64 configurations was performed. main arduousness addressed in is significant difference (in tons) values products. results show effect that occurs due different range values, one proposals made allows limitation be handled appropriately. summary, seeks provide essential information formulating efficient practical application.

Language: Английский

Integrating Machine Learning and Computational Intelligence for Green Manufacturing Processes DOI

P. Chitra,

R. Ananda Raja,

A. Ananthi

et al.

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 177 - 204

Published: Feb. 21, 2025

The chapter is focused on integrating machine learning and computational intelligence into green manufacturing processes. ML CI offer data-driven solutions toward industries strive for reduced environmental impacts through resource usage, energy consumption, waste reduction, among others. This will focus some very prominent algorithms, such as neural networks, reinforcement learning, fuzzy logic, their applications in predictive maintenance, process optimization, supply chain management sustainability. relates the integration of achieving eco-friendly goals—reduction carbon footprint improvement operational efficiency—through case studies practical examples. It discusses role played by digital twins, IoT integration, AI-driven decision-making enabling adaptive resilient systems. concluded future trends challenges to implement these technologies a larger scale transformation industry sustainable way.

Language: Английский

Citations

0
Trends and Opportunities in Sustainable Manufacturing: A Systematic Review of Key Dimensions from 2019 to 2024 DOI Open Access
Antonius Setyadi,

Sundari Soekotjo,

Setyani Dwi Lestari

et al.

Sustainability, Journal Year: 2025, Volume and Issue: 17(2), P. 789 - 789

Published: Jan. 20, 2025

Purpose: This systematic literature review analyzes trends, key findings, and research opportunities in manufacturing sustainability from 2019 to 2024, with a focus on the integration of emerging technologies socio-economic dimensions. Methodology: 181 publications was conducted, emphasizing technological advancements, gaps, influence global events sustainable manufacturing. Findings: highlights: (1) shift towards advanced like AI-driven circular economy solutions, digital twins, blockchain, which have demonstrated potential reduce energy consumption by 30% decrease material waste 20%, significantly enhancing outcomes; (2) persistent gaps addressing social, policy, regulatory dimensions; (3) role COVID-19 pandemic accelerating transformation reshaping priorities. Key findings also include PT Indocement achieving cumulative 35% reduction natural gas through sustained optimization initiatives 12% increase adoption among SMEs developing regions. Practical implications: strategic recommendations are provided for industry, policymakers, academics address regional disparities, ensuring 50% rates inclusive within regions over next five years, align efforts contexts. Originality: this presents comprehensive analysis current actionable insights, critical areas future research, highlighting that organizations adopting AI blockchain report up 25% improvement operational sustainability.

Language: Английский

Citations

0
Artificial Intelligence and Energy Market Quartile Spillovers: Implications for China's Renewable Energy and High Emission Sectors DOI

Zhengyu Ren,

Yujie Chen,

Shi-Jie Ma

et al.

Published: Jan. 1, 2025

Language: Английский

Citations

0
Smart Forecasting With AI DOI
Muhammad Usman Tariq

Advances in computational intelligence and robotics book series, Journal Year: 2025, Volume and Issue: unknown, P. 165 - 184

Published: Feb. 7, 2025

The use of smart forecasting in artificial intelligence (AI) to transform energy storage and consumption is examined this chapter. Artificial revolutionizing the systems industry particularly areas grids management renewable by analysing large volumes data finding patterns. In order predict generation maintain grid stability maximize chapter explores crucial roles that AI machine learning play. Additionally, it emphasizes how big data, can be combined increase accuracy which has important ramifications for sources like solar wind. effective commodity market operations demonstrated real-world case studies. Chapter also addresses ethical social issues deployment focusing on cooperation with human expertise.

Language: Английский

Citations

0
The Emerging Role of Artificial Intelligence in Enhancing Energy Efficiency and Reducing GHG Emissions in Transport Systems DOI Creative Commons
Tymoteusz Miller, Irmina Durlik, Ewelina Kostecka

et al.

Energies, Journal Year: 2024, Volume and Issue: 17(24), P. 6271 - 6271

Published: Dec. 12, 2024

The global transport sector, a significant contributor to energy consumption and greenhouse gas (GHG) emissions, requires innovative solutions meet sustainability goals. Artificial intelligence (AI) has emerged as transformative technology, offering opportunities enhance efficiency reduce GHG emissions in systems. This study provides comprehensive review of AI’s role optimizing vehicle management, traffic flow, alternative fuel technologies, such hydrogen cells biofuels. It explores potential drive advancements electric autonomous vehicles, shared mobility, smart transportation economic analysis demonstrates the viability AI-enhanced transport, considering Total Cost Ownership (TCO) cost-benefit outcomes. However, challenges data quality, computational demands, system integration, ethical concerns must be addressed fully harness potential. also highlights policy implications AI adoption, underscoring need for supportive regulatory frameworks policies that promote innovation while ensuring safety fairness.

Language: Английский

Citations

2
Using Fuzzy Logic to Analyse Weather Conditions DOI Open Access
Olga Małolepsza, Dariusz Mikołajewski, Piotr Prokopowicz

et al.

Electronics, Journal Year: 2024, Volume and Issue: 14(1), P. 85 - 85

Published: Dec. 28, 2024

Effective weather analysis is a very important scientific, social, and economic issue, because directly affects our lives has significant impact on various sectors, including agriculture, transport, energy, natural disaster management. Weather therefore the basis for operation of many decision-making support systems, especially in transport (air, sea), ensuring continuity supply chains industry or delivery food medicines, but also municipal economies tourism. Its role importance will grow with worsening climatic phenomena development Industry5.0 paradigm, which puts humans their environment at center attention. This article presents issues related to fuzzy sets systems model based them. The system was created using Matlab, Fuzzy Logic Designer application, focusing logic. With Designer, users can define sets, rules, carry out fuzzification defuzzification processes, thereby offering great possibilities data

Language: Английский

Citations

1
Artificial Neural Network Model to Predict the Exportation of Traditional Products of Colombia DOI Creative Commons

Andrea C. Gómez,

Lilian A. Bejarano, Helbert Espitia

et al.

Computation, Journal Year: 2024, Volume and Issue: 12(11), P. 221 - 221

Published: Nov. 4, 2024

This article develops the design, training, and validation of a computational model to predict exportation traditional Colombian products using artificial neural networks. work aims obtain single multilayer network. The number historical input data (delays), layers, neurons were considered for network design. In this way, an experimental design 64 configurations was performed. main arduousness addressed in is significant difference (in tons) values products. results show effect that occurs due different range values, one proposals made allows limitation be handled appropriately. summary, seeks provide essential information formulating efficient practical application.

Language: Английский

Citations

0