Relevant bibliographies by topics / Industrial chain optimization

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  1. Journal articles
  2. Dissertations / Theses
  3. Books
  4. Book chapters
  5. Conference papers

Academic literature on the topic 'Industrial chain optimization'

Author: Grafiati
Published: 7 June 2025
Last updated: 16 July 2025

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Journal articles on the topic "Industrial chain optimization"

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Luo, Haobo. "The Impact of Value Chain Embedding on Industrial Structure Optimization." Journal of Education, Humanities and Social Sciences 35 (July 4, 2024): 156–61. http://dx.doi.org/10.54097/rm5g2375.

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Value chain embedding refers to the participation of enterprises in the activities of the global value chain and the benefits derived from it. Existing studies have shown that value chain embedding can bring multiple benefits, including improving production efficiency, reducing costs, enhancing product quality, and innovation capabilities, among others. However, the specific impact of value chain embedding on industrial structure optimization is still controversial in current literature. This article analyzes the impact of value chain embedding from the perspectives of manufacturing industry,
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Alomar, Madani Abdu. "Performance Optimization of Industrial Supply Chain Using Artificial Intelligence." Computational Intelligence and Neuroscience 2022 (July 30, 2022): 1–10. http://dx.doi.org/10.1155/2022/9306265.

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Nowadays, organized retailing has witnessed a newer trend in the upcoming generations. Globally, these changes are attributed to growing family income, increased female participation, the transformation from joint to nuclear family structure, and technological advancements. Moreover, other variables such as lower supply chain costs, growing sales, rising consumer demands, changing market structure, and increasing competition also influenced supply chain networks. It is observed that the organizational nonlivestock supply chain performance is affected by strategic, operational, and environmenta
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Rybina, I. A., М. А. Goncharova, and S. S. Lomakin. "INDUSTRIAL SUPPLY CHAIN OPTIMIZATION TOOLS UNDER SANCTIONS PRESSURE." Вестник Алтайской академии экономики и права 2, no. 7 2024 (2024): 336–43. http://dx.doi.org/10.17513/vaael.3603.

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Zhou, Hang, Rui Qian Li, and Yue Yu. "Investigation of the Datamation of Manufacturing Industrial Chain in the Big Data Era." Applied Mechanics and Materials 670-671 (October 2014): 1629–32. http://dx.doi.org/10.4028/www.scientific.net/amm.670-671.1629.

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The big data era enable us to carry out data operations based on the extremely large data volumes to realize the datamation of manufacturing industrial chain. This provides us a good opportunity to optimize the manufacturing industrial chain and upgrade the development of manufacturing industry. In order to provide beneficial references for the optimization of manufacturing industrial chain and the development of manufacturing industry, in this paper, we explore new paths to realize the datamation of manufacturing industrial chain based on the big data era background. We also analyze the advan
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Bányai Tóth, Ágota. "Real-time supplier selection using digital twin technology: an Analytic Hierarchy Process-based optimization approach." Advanced Logistic Systems - Theory and Practice 18, no. 2 (2024): 97–107. http://dx.doi.org/10.32971/als.2024.021.

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Today, the selection of the optimal suppliers plays an increasingly important role in the efficient operation of supply chains. One of the main reasons for this is that the fourth industrial revolution has seen the emergence of increasingly complex supply chains, involving a growing number of suppliers to meet increasingly diversified customer needs. While manufacturing companies use framework contracts to secure the parts needed to meet uncertain customer needs, framework contracts often fix requirements for a fixed future period in the light of past supplier performance. The Fourth Industria
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Amol, Shenkar*1 &. Hredeya Mishra2. "METHODOLOGY CONCEPTS FLOW FOR DESIGN, MODELING AND ANALYSIS OF ROLLER CHAIN CONVEYOR SYSTEM." GLOBAL JOURNAL OF ENGINEERING SCIENCE AND RESEARCHES 5, no. 7 (2018): 239–43. https://doi.org/10.5281/zenodo.1313535.

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The basic aim of this Paper has been conducted on the most of the time conveyor chain is under tension which causes failure of chain assembly which is the major problem for industrial sector. Causes of this failure are improper design. It is important to study the influence of these parameters. All these parameters can be considered simultaneously and chain link design optimally. Optimization is the process of obtaining the best result under given circumstances in design of system. In optimization process we can find the conditions that give the maximum and minimum value of function. In this s
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Makarova, O. V. "Predictive method of inventory optimization in industrial manufacturer performance." E3S Web of Conferences 247 (2021): 01066. http://dx.doi.org/10.1051/e3sconf/202124701066.

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Strong collaboration in supply chain at B2B market may improve operational and financial performance of both suppliers and clients. Need for collaboration benefits realization is especially actual for supplying manufacturers with huge investments in inventory as well as high ordering and carrying costs. Traditional stock level optimization models rely on historic data which makes them inefficient when supply if influenced by changing customized demand of key B2B clients. Strong collaboration with key clients, synchronization of planning process through the whole supply chain up to the end user
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Hu, Xuhua, and Linyu Zhang. "Research on the integration level measurement and optimization path of industrial chain, innovation chain and service chain." Journal of Innovation & Knowledge 8, no. 3 (2023): 100368. http://dx.doi.org/10.1016/j.jik.2023.100368.

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Lin, Xuze. "Artificial Intelligence in the Industrial Engineering." Advances in Operation Research and Production Management 1, no. 1 (2024): 1–6. http://dx.doi.org/10.54254/3006-1210/direct/0106.

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The integration of Artificial Intelligence (AI) into industrial engineering, epitomized by the advent of Industry 4.0, has reshaped manufacturing landscapes. This article explores the profound impact of AI over the past decade, focusing on predictive maintenance, operational optimization, robotics, quality control, and supply chain management. Predictive maintenance, facilitated by machine learning algorithms, minimizes downtime and optimizes resource allocation. Operational optimization, achieved through AI's real-time data analysis, enhances decision-making, resource utilization, and overall
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Lisienkova, Liubov. "A method for optimisation of enterprise logistic supply chain." MATEC Web of Conferences 239 (2018): 03009. http://dx.doi.org/10.1051/matecconf/201823903009.

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The aim of the study was to develop an optimisation method for management of current assets of an industrial enterprise by the concept of logistics supply chains. The ways of acceleration of working capital turnover at the stages of supply, production and marketing of goods and services have been identified. The necessity of applying the concept of supply chain management to working capital management has been justified. This allowed defining the management principles in the supply chain of an industrial enterprise. As a result, a method for optimization of enterprise current assets of an indu
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Dissertations / Theses on the topic "Industrial chain optimization"

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Eks̜ioğlu, Burak. "Network algorithms for supply chain optimization problems." [Gainesville, Fla.] : University of Florida, 2002. http://purl.fcla.edu/fcla/etd/UFE0000528.

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Dacha, Fred (Frederick Omondi), and Li Jin. "Supply chain network optimization : low volume industrial chemical product." Thesis, Massachusetts Institute of Technology, 2013. http://hdl.handle.net/1721.1/81096.

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Thesis (M. Eng. in Logistics)--Massachusetts Institute of Technology, Engineering Systems Division, 2013.<br>Cataloged from PDF version of thesis.<br>Includes bibliographical references (p. 60-62).<br>The chemical industry is a highly competitive and low margin industry. Chemical transportation faces stringent safety regulations meaning that Cost-To-Serve (C2S), costs associated with products net flow from manufacturers to customers, consists of a big percentage of the delivered product cost. Supply chain practitioners in this industry need to make key logistics decisions to minimize C2S for p
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Gunnarsson, Helene. "Supply chain optimization in the forest industry /." Linköping : Department of Mathematics, Linköpings universitet, 2007. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-8856.

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Gunpinar, Serkan. "Supply Chain Optimization of Blood Products." Scholar Commons, 2013. http://scholarcommons.usf.edu/etd/4684.

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Major challenges in the management of blood supply chain are related to the shortage and wastage of the blood products. Given the perishability characteristics of blood which can be stored up to a limited number of days, if hospitals and blood centers keep an excessive number of blood units on inventory, wastages may occur. On the other hand, if sufficient number of blood units are not stored on inventory, shortages of this resource may cause the cancellations of important activities and increase the fatality rates at hospitals. Three mathematical models have been developed with the goal to im
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Pujari, Nikhil Ajay. "Integrated Supply Chain Optimization Model Using Mathematical Programming and Continuous Approximation." Ohio University / OhioLINK, 2005. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1132114913.

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Keskin, Burcu Baris. "Joint optimization of location and inventory decisions for improving supply chain cost performance." [College Station, Tex. : Texas A&M University, 2007. http://hdl.handle.net/1969.1/ETD-TAMU-2528.

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Arayapan, Khanittha, and Piyanut Warunyuwong. "Logistics Optimization: Application of Optimization Modeling in Inbound Logistics." Thesis, Mälardalen University, School of Innovation, Design and Engineering, 2009. http://urn.kb.se/resolve?urn=urn:nbn:se:mdh:diva-6213.

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<p><p>To be a market leader, low cost and responsiveness are the key success factors. Logistics activities create high cost reducing competitiveness of the company, especially for the remote production base. Thus, logistics activities which are delivery planning, freight forwarder and delivery mode selection must be optimized. The focusing area of this paper is inbound logistics due to its big proportion in the total cost and involvement with several stakeholders. The optimization theory and Microsoft Excel’s Solver is used to create the standard optimization tools since it is an efficient and
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Mysyk, Jessica Marie. "Supply Chain Operations Planning in a Carbon Cap and Trade Market." Bowling Green State University / OhioLINK, 2020. http://rave.ohiolink.edu/etdc/view?acc_num=bgsu1587675401823912.

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Romero, Rodriguez Daniel. "Physical and Social Systems Resilience Assessment and Optimization." Scholar Commons, 2018. https://scholarcommons.usf.edu/etd/7359.

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Resilience has been measured using qualitative and quantitative metrics in engineering,economics, psychology, business, ecology, among others. This dissertation proposes a resilience metric that explicitly incorporates the intensity of the disruptive event to provide a more accurate estimation of system resilience. A comparative analysis between the proposed metric and average performance resilience metrics for linear and nonlinear loss and recovery functions suggests that the new metric enables a more objective assessment of resilience for disruptions with different intensities. Moreover, the
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Huang, Jing. "Resource Management and Sourcing Strategies in Supply Chain Coordination under an Uncertain Environment." Ohio University / OhioLINK, 2012. http://rave.ohiolink.edu/etdc/view?acc_num=ohiou1354756891.

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Books on the topic "Industrial chain optimization"

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Joseph, Geunes, ed. Applications of supply chain management and e-commerce research. Springer, 2005.

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Mischenko, Aleksandr. Optimization models of investment management in logistics. INFRA-M Academic Publishing LLC., 2022. http://dx.doi.org/10.12737/1839692.

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The textbook is devoted to planning and modeling of investment projects for the development of logistics infrastructure and supply chain management. Both theoretical models of investment management in logistics and practical examples of the use of the proposed methodology in the selection of optimal production programs of the enterprise, management of wholesale purchases of trading firms, analysis of the effectiveness of projects for the creation of warehouse infrastructure, working capital management in the procurement of material resources in industrial logistics are presented.&#x0D; For und
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service), SpringerLink (Online, ed. Relational Supply Contracts: Optimal Concessions in Return Policies for Continuous Quality Improvements. Springer-Verlag Berlin Heidelberg, 2010.

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(Editor), Joseph Geunes, and Panos M. Pardalos (Editor), eds. Supply Chain Optimization (Applied Optimization). Springer, 2005.

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Pardalos, P. M. Supply Chain Optimization. Springer, 2006.

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Pardalos, P. M. Supply Chain Optimization. Springer, 2010.

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Supply Chain Management: Models, Applications, and Research (Applied Optimization). Springer, 2002.

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Choi, Tsan-Ming. Fashion Retail Supply Chain Management: A Systems Optimization Approach. Taylor & Francis Group, 2014.

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Lawrence, Kenneth D. Supply Chain in Manufacturing, Distribution, and Transportation: Modeling, Optimization, and Applications. Taylor & Francis Group, 2011.

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Fashion Retail Supply Chain Management: A Systems Optimization Approach. Taylor & Francis Group, 2017.

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Book chapters on the topic "Industrial chain optimization"

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Cevallos, Carlos, Mario Peña, and Lorena Siguenza-Guzman. "New Hybrid Algorithm for Supply Chain Optimization." In Innovations in Industrial Engineering. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-78170-5_25.

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Ficko, Mirko, Simon Klancnik, Simon Brezovnik, Joze Balic, Miran Brezocnik, and Tone Lerher. "Intelligent Optimization Methods for Industrial Storage Systems." In Warehousing in the Global Supply Chain. Springer London, 2012. http://dx.doi.org/10.1007/978-1-4471-2274-6_13.

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Pandit, Abhijit, and Ramakant Bhardwaj. "Models of Supply Chain Sustainability in Industrial Engineering." In Applications of Advanced Optimization Techniques in Industrial Engineering. CRC Press, 2022. http://dx.doi.org/10.1201/9781003089636-14.

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Wang, Huan-pei, Bing-nan Liu, and Xiao-feng Dong. "The Recognition and Optimization of the Critical Chain." In The 19th International Conference on Industrial Engineering and Engineering Management. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38427-1_41.

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Khan, Pathan Afthab, Vinay Teja Ravada, Manohar Tumna, Sai Suresh Vidiyala, and Srinivas Rao Tatavarthy. "A Supply Chain Study of Managing Multiple Routes Thru Ant Colony Optimization." In Recent Advances in Industrial Machines and Mechanisms. Springer Nature Singapore, 2024. http://dx.doi.org/10.1007/978-981-99-4270-1_60.

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Gao, Ya-qun. "Research on Reliability Allocation and Optimization of Logistics Supply Chain." In International Asia Conference on Industrial Engineering and Management Innovation (IEMI2012) Proceedings. Springer Berlin Heidelberg, 2013. http://dx.doi.org/10.1007/978-3-642-38445-5_123.

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Kumar, Vimal, Ajay Jha, Pratima Verma, and Nagendra Kumar Sharma. "The Tradeoff in Managing Overall Cost and Backorder Minimization in Two-Stage Multi Commodity Supply Chain Problem." In Applications of Advanced Optimization Techniques in Industrial Engineering. CRC Press, 2022. http://dx.doi.org/10.1201/9781003089636-4.

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Wan, Jie, Rui-ceng Meng, and Rui-xue Shan. "Robust Optimization Model for a Food Supply Chain Under Uncertainty." In Proceedings of the 22nd International Conference on Industrial Engineering and Engineering Management 2015. Atlantis Press, 2016. http://dx.doi.org/10.2991/978-94-6239-180-2_66.

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Vamsikrishna, A., Adiga M. Manoj, Anurag V. Rao, and Sharma S. G. Divya. "Decision making in a supply chain for optimization of transportation cost." In Challenges and Opportunities in Industrial and Mechanical Engineering: A Progressive Research Outlook. CRC Press, 2024. http://dx.doi.org/10.1201/9781032713229-30.

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Gagandeep, Rahul O. Vaishya, and R. S. Walia. "Prioritizing the Drivers of Green Supply Chain Management Using ISM-Fuzzy-MICMAC Analysis." In Advances in Modelling and Optimization of Manufacturing and Industrial Systems. Springer Nature Singapore, 2023. http://dx.doi.org/10.1007/978-981-19-6107-6_4.

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Conference papers on the topic "Industrial chain optimization"

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Li, Zhe, Yiqiang Zhang, Hanshu Bi, Hongli Guan, and Zhiyuan Li. "Intelligent Optimization of Material Supply Chain via Machine Learning." In 2024 International Conference on Industrial IoT, Big Data and Supply Chain (IIoTBDSC). IEEE, 2024. https://doi.org/10.1109/iiotbdsc64371.2024.00017.

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Zhao, Chuanqi, Lanruo Wang, Qizhe Zhang, and Rui Song. "Resource Scheduling and Optimization Strategy in Edge Computing Environment." In 2024 International Conference on Industrial IoT, Big Data and Supply Chain (IIoTBDSC). IEEE, 2024. https://doi.org/10.1109/iiotbdsc64371.2024.00077.

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Liu, Hanfei. "Food Nutrition Optimization and Prediction System Based on Intelligent Algorithm." In 2024 International Conference on Industrial IoT, Big Data and Supply Chain (IIoTBDSC). IEEE, 2024. https://doi.org/10.1109/iiotbdsc64371.2024.00083.

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Pham, Quang Nhat, Tran Hong Phuong Pham, Thi Yen Vi Ngo, and Duc Duy Nguyen. "A novel optimization model for apparel closed-loop supply chain planning." In 2024 International Conference on Logistics and Industrial Engineering (ICLIE). IEEE, 2024. https://doi.org/10.1109/iclie61478.2024.11015370.

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Zhang, Pei. "Optimization and Implementation of Intelligent Scheduling Algorithms in the Civil Aviation Supply Chain." In 2024 International Conference on Industrial IoT, Big Data and Supply Chain (IIoTBDSC). IEEE, 2024. https://doi.org/10.1109/iiotbdsc64371.2024.00063.

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Jiang, Yutong. "Optimization of Higher Vocational English Teaching Design Based on Optimizing Apriori Algorithm." In 2024 International Conference on Industrial IoT, Big Data and Supply Chain (IIoTBDSC). IEEE, 2024. https://doi.org/10.1109/iiotbdsc64371.2024.00073.

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Song, Mingshu, Xiaolei Ma, Pengfei Duan, Yandong Yang, and Qiang Zhou. "Optimization and Implementation of Deep Learning Algorithm in Power Dispatch Speech Recognition." In 2024 International Conference on Industrial IoT, Big Data and Supply Chain (IIoTBDSC). IEEE, 2024. https://doi.org/10.1109/iiotbdsc64371.2024.00022.

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Gao, Fangyu, Di Chen, Shuai Yang, Zhenghu Hao, Qiong Wu, and Xu Zhang. "Big Data-Driven Scientific and Technological Innovation Mechanism Optimization and Decision Support System." In 2024 International Conference on Industrial IoT, Big Data and Supply Chain (IIoTBDSC). IEEE, 2024. https://doi.org/10.1109/iiotbdsc64371.2024.00047.

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Chen, Yan, and Songxian Liu. "Study of Joint Optimization Algorithm for SVR Parameter and Feature Selection Based on Improved AGA." In 2024 International Conference on Industrial IoT, Big Data and Supply Chain (IIoTBDSC). IEEE, 2024. https://doi.org/10.1109/iiotbdsc64371.2024.00084.

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Li, Kejun, Yifei Shen, and Nan Jia. "Optimization of a big data-driven public security policy and regulation Q&A system." In 2024 International Conference on Industrial IoT, Big Data and Supply Chain (IIoTBDSC). IEEE, 2024. https://doi.org/10.1109/iiotbdsc64371.2024.00043.

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