Scaling of Hardware-Compatible Perturbative Training Algorithms

Engineering, Electrical Engineering, Information Science, Electronic Information, Computer Science, Artificial Intelligence,
perturbative training   hardware compatibility   gradient estimation   stochastic gradient descent   neuromorphic hardware   machine learning   computational efficiency  

With the rapid development of artificial intelligence (AI) technology, artificial neural networks (ANNs) have achieved significant success in multiple fields. However, traditional neural network training methods—especially the backpropagation algorithm—face numerous challenges in hardware implementation. Although the backpropagation algorithm is ef...

Learning Semantic Consistency for Audio-Visual Zero-Shot Learning

Information Science, Computer Science, Artificial Intelligence,
Audio-Visual Zero-Shot Learning   Video Classification   Attention Mechanism   Hyperbolic Geometry   Semantic Consistency  

Academic Background In the field of artificial intelligence, Zero-Shot Learning (ZSL) is an extremely challenging task that aims to recognize unseen classes by leveraging knowledge from seen classes. Audio-Visual Zero-Shot Learning (AVZSL), a branch of ZSL, seeks to classify unseen classes by combining audio and visual information. However, many ex...

Comparative Analysis of Methodologies and Approaches in Recommender Systems Utilizing Large Language Models

Information Science, Computer Science, Artificial Intelligence,
Recommender Systems   Large Language Models   Natural Language Processing   User Modeling   Collaborative Filtering   Parameter-Efficient Fine-Tuning  

Academic Background With the explosive growth of internet information, recommender systems (RSs) have become indispensable in modern digital life. Whether it’s movie recommendations on Netflix or personalized news feeds on social media, recommender systems are reshaping users’ online experiences. However, traditional recommender systems face numero...

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...

Dombi Weighted Geometric Aggregation Operators on the Class of Trapezoidal-Valued Intuitionistic Fuzzy Numbers and Their Applications to Multi-Attribute Group Decision-Making

Information Science, Computer Science, Artificial Intelligence,
Trapezoidal-valued intuitionistic fuzzy numbers   Dombi weighted geometric aggregation operators   Multi-attribute group decision-making   Photovoltaic site selection   Sensitivity analysis  

Academic Background In modern engineering and management fields, decision-making problems are often accompanied by uncertainty and ambiguity. Traditional fuzzy set theory has certain limitations when dealing with these issues, especially in complex Multi-Attribute Group Decision-Making (MAGDM) problems. Intuitionistic Fuzzy Set (IFS), as an extende...

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...