Fast Machine Learning for Building Management Systems

Engineering, Architecture and Civil Engineering, Electrical Engineering, Information Science, Artificial Intelligence,
Fast Machine Learning   Building Management Systems   Energy Forecasting   Hardware Accelerators   Building Automation  

Academic Background With the intensification of the global energy crisis and the increasing awareness of environmental protection, the intelligence and efficiency of Building Management Systems (BMS) have become a focal point in both academia and industry. Traditional BMS relies on rule-based control methods, which are unable to dynamically adapt t...

Enhancing Decentralized Energy Storage Investments with Artificial Intelligence-Driven Decision Models

Chemistry, Energy Chemistry, Engineering, Environmental Engineering, Energy Engineering, Information Science, Artificial Intelligence,
decentralized energy storage   energy investments   energy efficiency   Q-learning   molecular fuzzy sets  

Academic Background As the global energy structure transitions towards renewable energy, the importance of decentralized energy storage is becoming increasingly prominent. Unlike traditional centralized energy storage systems, decentralized energy storage localizes the energy production and storage processes, reducing the risk of large-scale system...

Power Aggregation Operators Based on Aczel-Alsina T-Norm and T-Conorm for Intuitionistic Hesitant Fuzzy Information and Their Application to Logistics Service Provider Selection

Engineering, Transportation Engineering, Information Science, Computer Science, Artificial Intelligence,
Power Aggregation Operators   Decision-Making Technique   Intuitionistic Hesitant Fuzzy Sets   Logistics Service Provider Selection   Aczel-Alsina T-Norm  

Academic Background In modern supply chain management, the selection of logistics service providers is a complex and critical issue. Enterprises need to evaluate and choose third-party organizations capable of efficiently managing and executing logistics tasks. However, the decision-making process in reality often involves significant uncertainty a...

A Systematic Survey of Hybrid ML Techniques for Predicting Peak Particle Velocity (PPV) in Open-Cast Mine Blasting Operations

Engineering, Mining and Metallurgical Engineering, Environmental Engineering, Information Science, Computer Science, Artificial Intelligence,
Peak Particle Velocity   Machine Learning   Ground Vibration   Air Over Pressure   Flyrock  

Blasting operations in open-cast mines are crucial for mineral extraction but also come with significant environmental and structural risks. The peak particle velocity (PPV) generated during blasting is a key metric for assessing the impact of blasting vibrations on surrounding structures and the environment. Accurate PPV prediction is essential fo...

Pythagorean Linguistic Information-Based Green Supplier Selection Using Quantum-Based Group Decision-Making Methodology and the MULTIMOORA Approach

Engineering, Environmental Engineering, Information Science, Computer Science, Artificial Intelligence,
Pythagorean Linguistic Set   MULTIMOORA   Quantum Probability Theory   Multi-Criteria Group Decision-Making   Green Supplier Selection  

With the increasing severity of global environmental issues, companies are placing greater emphasis on green and sustainable development in supply chain management. Green Supply Chain Management (GSCM) has become a crucial means for enterprises to enhance competitiveness and achieve sustainable development. However, Green Supplier Selection (GSS) i...