Abstract.The current recommendation application scenario is more complex, and the traditional recommendation algorithm can no longer meet the needs of user diversity. To solve this problem, this paper proposes an improved multi-objective optimization recommendation model based on knowledge graph to optimize four recommendation goals of novelty, diversity, accuracy and recall simultaneously. A user preference set is constructed based on user behavioral preferences and item-related characteristics before recommendation, which provides the basis for subsequent recommendations. Two improved algorithms are … Read more →

Abstract.Humanoid robots, as the core carriers of embodied intelligence, are moving from specialized scenarios to general-purpose applications. The incorporation of large language models (LLMs) endows them with cognitive and decision-making capabilities similar to those of a human "brain," becoming a key enabler for technological breakthroughs. Based on the practical and technological achievements of the global humanoid robot industry from 2024 to 2025, this paper systematically analyzes the technical value and practical bottlenecks of LLMs as robot brains. The study finds that, through semantic … Read more →

Abstract.When AI is currently applied to complex scenarios, it only processes single information such as text and images, which cannot meet people's needs to "perceive things as they do." Instead, multimodal learning, which can integrate different information such as text, images, audio, and video, has become a key direction for the development of generative AI. However, the current multimodal applications of generative AI are still stuck in several hurdles: First, the different modalities are quite different. For example, text is segmented and images are pixelated, which can easily cause problems when … Read more →

Abstract.Real-time regulation of water-flooding injection–production systems is a crucial factor in enhancing reservoir development efficiency. However, in practical water-flooding operations, reservoir heterogeneity causes the inter-well fluid connectivity to vary dynamically over time. As a result, conventional regulation methods often require a considerable amount of time to adjust control schemes, leading to significant lag effects. When oilfields enter the medium- to high-water-cut stage, the geological structures and flow patterns become increasingly complex, making it difficult for traditional … Read more →

Abstract.The rapid development of artificial intelligence technology is driving fundamental changes in the field of digital marketing, bringing innovation opportunities and transformation challenges to enterprises. This study focuses on the core innovation mode of digital marketing driven by artificial intelligence and its corresponding enterprise transformation path. Through in-depth analysis of key modes such as data-driven personalized access, predictive pre-layout and real-time closed-loop optimization, this paper reveals the internal logic of the evolution of marketing activities towards … Read more →

Abstract.With the acceleration of urbanization in China, the management of urban household waste is facing severe challenges. Optimizing and scheduling the path of garbage classification and transportation has become the key to improving efficiency and reducing costs. This article is based on the Vehicle Routing Problem (CVRP) model and combines multi-objective optimization methods to study complex scenarios involving single vehicles, multi vehicle collaboration, and intermediate stations. This article establishes a CVRP model with capacity constraints and uses greedy algorithm to generate paths, … Read more →

Abstract.As a crucial component of enterprise supply chain management, Distribution Requirements Planning (DRP) directly impacts product distribution efficiency, inventory control levels, and customer responsiveness. Traditional DRP rating evaluation methods, which predominantly rely on expert experience and static analysis, exhibit issues such as excessive subjectivity and poor dynamic adaptability, making them inadequate for modern complex supply network demands. To address these challenges, this study proposes an AI-powered intelligent DRP rating evaluation model. By integrating machine learning … Read more →

Abstract.Urban traffic congestion has become a common problem faced by major cities around the world. How to improve the resilience of urban transportation systems and alleviate urban traffic congestion issues urgently needs to be addressed. Therefore, taking the resilience of the urban transportation system as the topic, selecting the overall transportation system of Guangzhou as the research object, exploring the resilience of the entire Guangzhou transportation system, and proposing an evaluation model to handle uncertainty and ambiguity. Firstly, by analyzing the resilience of urban transportation … Read more →

Abstract.With the rapid development of the e-commerce industry, the demand for logistics has increased sharply, and the management efficiency issues of sorting centers have become increasingly prominent. This article provides daily and hourly cargo volume predictions, transportation route optimization, and staff scheduling for 57 centers over the next 30 days to meet user demands and transmission speed requirements. This paper proposes a comprehensive framework that combines the LSTM-ARIMA model for cargo volume prediction, calculates the cargo volume change rate based on the actual sorting center data … Read more →

Abstract.The rapid advancement of the digital economy and smart shipping has precipitated a growing demand for interdisciplinary professionals who possess both information technology expertise and maritime business literacy. However, the current vocational education system exhibits a misalignment with industrial needs, particularly in curriculum content, pedagogical models, and faculty competency. The emergence of Generative Artificial Intelligence (GenAI) provides a novel avenue for the intelligent transformation of vocational education, enabling personalized learning, dynamic curriculum generation, … Read more →