Design of a multi-agent system for distributed voltage regulation

In this paper, an intelligent distributed multi-agent system (MAS) is proposed for the implementation of a novel optimization technique for distributed voltage regulation. The proposed MAS approach controls a large heavily-meshed distribution network which is grouped into small subnetworks using ε decomposition. The voltage regulation is accomplished by distributed generator (DG) agents, linear programming solver (LPS) agents, network violation detector (NVD) agents, and one ε decomposition agent. The LPS agent has an embedded control algorithm which optimizes DG generation within a subnetwork once the voltage at particular nodes exceeds the normal operational limits. The subnetworks and their control requirements are achieved through self-organization, which is the novelty of the research. Each intelligent agent has its own knowledge and reasoning logic to plan its own activities. The control actions are coordinated through agent communications within the subnetwork. The agent platform, Presage2, with improved autonomy and agent communication capability, has been used to develop the proposed MAS system and design the agents’ behaviors

The combined effect of foreign direct investment on firm productivity

This paper attempts to answer the economic implications of combining inward foreign direct investment (IFDI) and outward foreign direct investment (OFDI) by constructing a panel fixed effects model using Chinese industrial firm-level data for the period 1998–2013. Specifically, we focus on the impact of combining IFDI and OFDI on firm productivity in China. We also introduce interactive terms into the model to explore the direct and indirect mechanisms through which IFDI and OFDI affect productivity growth. The results show that IFDI and OFDI work together to contribute to productivity growth by acting directly on the level of technology, thereby increasing productivity. IFDI intensifies market concentration, which in turn positively moderates the relationship between OFDI and productivity. Furthermore, IFDI moderates the financing constraints of firms, but has a weaker effect; the easing of financing constraints facilitates the positive impact of OFDI on productivity. Absorptive capacity favours IFDI spillover, but OFDI inhibits absorptive capacity improvements. Our in-depth analysis of the mechanism of the combined impact of IFDI and OFDI on productivity reveals the objectives of using this combination, thereby providing theoretical support and policy recommendations for the implementation of this strategy

Hybrid Base Complex: Extract and Visualize Structure of Hex-dominant Meshes

Hex-dominant mesh generation has received significant attention in recent research due to its superior robustness compared to pure hex-mesh generation techniques. In this work, we introduce the first structure for analyzing hex-dominant meshes. This structure builds on the base complex of pure hex-meshes but incorporates the non-hex elements for a more comprehensive and complete representation. We provide its definition and describe its construction steps. Based on this structure, we present an extraction and categorization of sheets using advanced graph matching techniques to handle the non-hex elements. This enables us to develop an enhanced visual analysis of the structure for any hex-dominant meshes.We apply this structure-based visual analysis to compare hex-dominant meshes generated by different methods to study their advantages and disadvantages. This complements the standard quality metric based on the non-hex element percentage for hex-dominant meshes. Moreover, we propose a strategy to extract a cleaned (optimized) valence-based singularity graph wireframe to analyze the structure for both mesh and sheets. Our results demonstrate that the proposed hybrid base complex provides a coarse representation for mesh element, and the proposed valence singularity graph wireframe provides a better internal visualization of hex-dominant meshes.Comment: accepted by IEEE Transactions on Visualization and Computer Graphic

Knowledge-enhanced Iterative Instruction Generation and Reasoning for Knowledge Base Question Answering

Multi-hop Knowledge Base Question Answering(KBQA) aims to find the answer entity in a knowledge base which is several hops from the topic entity mentioned in the question. Existing Retrieval-based approaches first generate instructions from the question and then use them to guide the multi-hop reasoning on the knowledge graph. As the instructions are fixed during the whole reasoning procedure and the knowledge graph is not considered in instruction generation, the model cannot revise its mistake once it predicts an intermediate entity incorrectly. To handle this, we propose KBIGER(Knowledge Base Iterative Instruction GEnerating and Reasoning), a novel and efficient approach to generate the instructions dynamically with the help of reasoning graph. Instead of generating all the instructions before reasoning, we take the (k-1)-th reasoning graph into consideration to build the k-th instruction. In this way, the model could check the prediction from the graph and generate new instructions to revise the incorrect prediction of intermediate entities. We do experiments on two multi-hop KBQA benchmarks and outperform the existing approaches, becoming the new-state-of-the-art. Further experiments show our method does detect the incorrect prediction of intermediate entities and has the ability to revise such errors.Comment: Accepted by NLPCC 2022(oral