Relevant bibliographies by topics / Logistics Regression

Contents

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

Academic literature on the topic 'Logistics Regression'

Author: Grafiati
Published: 4 June 2021
Last updated: 25 July 2025

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Journal articles on the topic "Logistics Regression"

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Qiu, Qixuan. "Based on Bayesian Regression and Logistic Regression Model Forecast Logistics Transportation Delay." Applied and Computational Engineering 135, no. 1 (2025): 175–83. https://doi.org/10.54254/2755-2721/2025.21217.

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In the logistics supply chain transportation, it is inevitable to encounter some unpredictable risks, these risks will greatly affect the accuracy and timeliness of logistics transportation, in order to explore the problem of logistics transport delays, this article uses Bayesian regression and logistic regression to establish a model, by analyzing the relationship between the journey risk and the logistics transport delays, Bayesian regression through Mean Squared Error(MSE) and R carry out a test, logistic regression through Accuracy, Receiver Operating Characteristic Curve (ROC Curve) and P
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Li, Biwei. "Factors Affecting the Punctuality of Logistics Services Using Binary Logistic Regression." BCP Business & Management 34 (December 14, 2022): 704–12. http://dx.doi.org/10.54691/bcpbm.v34i.3085.

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The Indian logistics industry is in a period of rapid development. The purpose of this study is to analyze the factors affecting the punctuality of trucks for logistics distribution services in India based on data analysis. The data comes from 6880 pieces of data from the VTS data platform. A binary regression model was established for data analysis, and the model was tested to ensure statistical significance. Binary logistic regression was used to examine truck types, geographic locations, commodity types, order types, and suppliers for logistics services to examine significant differences be
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Iman, Youssif Ibrahim, and Sedqi Kareem Omar. "Email Spam Classification Based on Logistics Regression." Engineering and Technology Journal 10, no. 05 (2025): 4847–54. https://doi.org/10.5281/zenodo.15378605.

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Email is a common communication tool used by both individuals and organizations. It involves a variety of interactions, including file sharing. In addition to the advantages it provides, there is the uninvited email sharing. This unsolicited email is referred to as "spam." Malicious content like viruses, phishing scams, and unsolicited ads can be found in spam. It is well known that communication security is crucial. In order to filter email systems for malicious tools or software, it is essential to classify them based on a variety of criteria. In these kinds of classification studies, machin
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Hussein, Dima Talaso, and Felister Mutoka. "Factors Affecting Logistics Performance Metrics in Logistics Industry: Case of Kuehne+Nagel Logistics Company." Journal of Procurement & Supply Chain 1, no. 1 (2021): 1–15. http://dx.doi.org/10.70619/vol1iss1pp1-15.

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The purpose of this study was to determine the role of logistics metrics on logistics performance measurement in the Kenyan logistics industry; a case study of Kuehne Nagel logistic company. The specific objectives were to determine the role of logistics cost, logistics quality, logistics productivity, and logistics cycle-time on logistics performance measurement in Kuehne Nagel logistic company. The study was anchored on the SCOR model, resource-based view, theory of constraints and transactions theory. The study adopted a descriptive research design. The study target population was 72 manage
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El Yadari, Manal, Fouad Jawab, Imane Moufad, and Jabir Arif. "Logistics Sprawl and Urban Congestion Dynamics Toward Sustainability: A Logistic Regression and Random-Forest-Based Model." Sustainability 17, no. 13 (2025): 5929. https://doi.org/10.3390/su17135929.

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Increasing road congestion is the main constraint that may influence the economic development of cities and urban freight transport efficiency because it generates additional costs related to delay, influences social life, increases environmental emissions, and decreases service quality. This may result from several factors, including an increase in logistics activities in the urban core. Therefore, this paper aims to define the relationship between the logistics sprawl phenomenon and congestion level. In this sense, we explored the literature to summarize the phenomenon of logistics sprawl in
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özcan, Sezgin. "A Study on Casualty Profile Using Logistics Regression." Journal of Military and Information Science 2, no. 1 (2014): 3. http://dx.doi.org/10.17858/jmisci.25688.

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Eljaji, Halah, and Remudin Reshid Mekuria. "MATHEMATICAL MODELS AND ALGORITHMS IN LOGISTICS: REAL- WORLD APPLICATIONS AND AI IMPACT." Alatoo Academic Studies 24, no. 2 (2024): 412–21. http://dx.doi.org/10.17015/aas.2024.242.33.

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Have you ever pondered the importance of mathematics in the field of logistics? Have you also reflected on whether a solid understanding of mathematical principles is crucial for achieving success in a logistics profession? This article explores the intersection of mathematics and logistics, shedding light on the indispensable role mathematics plays within the industry. By exploring practical applications, it provides insights into the mathematical concepts integral to the daily activities of logistics professionals. Whether aspiring to enter the field or carrying out further studies in logist
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Basalim, Said, Danang Parikesit, Sigit Priyanto, and Muhammad Zudhy Irawan. "Shipment Size Analysis on Cross-Border Freight Transportation Using Stereotype Logistic Regression: Case Study Between West Kalimantan, Indonesia and Sarawak, Malaysia." International Journal on Advanced Science, Engineering and Information Technology 15, no. 1 (2025): 180–88. https://doi.org/10.18517/ijaseit.15.1.19357.

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Cross-border freight transport is vital for regional logistics, facilitating trade between neighboring countries. However, inefficiencies in shipment size decisions, such as overloading or underutilizing vehicles, can lead to increased costs and logistical challenges. This study investigates the key factors influencing shipment size decisions in the West Kalimantan (Indonesia)–Sarawak (Malaysia) cross-border corridor. Data from 2,017 truck trips conducted between 2016 and 2018, provided by the Fish Quarantine and Inspection Agency, was used for the analysis. Ordinal logistic regression methods
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Zhao, Shuya. "Research on Logistics Cost Prediction Based on Random Forest Regression Modeling." Transactions on Economics, Business and Management Research 11 (November 5, 2024): 367–76. https://doi.org/10.62051/mv8p5485.

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With the rapid development of globalization and e-commerce, logistics industry has become a key link between production and consumption. However, the efficient management and control of logistics costs has become an important challenge for enterprises to enhance their competitiveness. The scientific control of logistics cost depends on accurate cost prediction. In this paper, we first process the missing values of open source logistics cost data, and analyze the logistics cost and numerical influencing factors as skewed distribution with the help of distribution probability density plot and hi
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D. I. Golubtsov, R. B. Sartova, Z. B. Akhmetova, and A. B. Alikbayeva. "INFLUENCE OF DIGITAL TECHNOLOGIES ON THE LOGISTICS PERFORMANCE INDICATORS IN KAZAKHSTAN." Bulletin of Toraighyrov University. Economics series, no. 4.2024 (December 26, 2024): 134–44. https://doi.org/10.48081/uryb4762.

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Currently, digital transformation in the sphere of logistics activities has reached a new level. Logistics organisations in the context of the Republic of Kazakhstan are also striving to optimise business processes at the level of their enterprises by resorting to the implementation of advanced digital technologies. This article examines the impact of digital solutions on the performance of logistics organisations in Kazakhstan through regression analysis. The target data was collected within the framework of the dissertation research on the topic: “Digital Transformation of functioning of the
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Dissertations / Theses on the topic "Logistics Regression"

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Laird, Daniel T. "Logistics Regression Model on Antenna Control Unit Autotracking Mode." International Foundation for Telemetering, 2015. http://hdl.handle.net/10150/596414.

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ITC/USA 2015 Conference Proceedings / The Fifty-First Annual International Telemetering Conference and Technical Exhibition / October 26-29, 2015 / Bally's Hotel & Convention Center, Las Vegas, NV<br>Over the past several years DoD imposed constraints on test deliverables, requiring objective measures of test results, i.e., statistically defensible test and evaluation (SDT&E) methods and results. These constraints force testers to employ statistical hypotheses, analyses and modeling to assess test results objectively, i.e., based on statistical metrics, analytical methods, probability of confi
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Lind, Nilsson Rasmus. "Machine learning in logistics : Increasing the performance of machine learning algorithms on two specific logistic problems." Thesis, Luleå tekniska universitet, Institutionen för system- och rymdteknik, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:ltu:diva-64761.

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Data Ductus, a multination IT-consulting company, wants to develop an AI that monitors a logistic system and looks for errors. Once trained enough, this AI will suggest a correction and automatically right issues if they arise. This project presents how one works with machine learning problems and provides a deeper insight into how cross-validation and regularisation, among other techniques, are used to improve the performance of machine learning algorithms on the defined problem. Three techniques are tested and evaluated in our logistic system on three different machine learning algorithms, n
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Schumacher, Joseph F. "Forecasting retention in the United States Marine Corps Reserve." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2005. http://library.nps.navy.mil/uhtbin/hyperion/05Mar%5FSchumacher.pdf.

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Skácel, Zdeněk. "Posouzení výkonnosti firmy ČSAD Kyjov Logistics a.s." Master's thesis, Vysoké učení technické v Brně. Fakulta podnikatelská, 2015. http://www.nusl.cz/ntk/nusl-225019.

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Master's thesis deals with the assessment of financial performance of the company ČSAD Kyjov Logistics a.s. The theoretical part explains the theoretical basis of financial analysis, regression analysis, the issue of time series, correlation analysis and benchmarking. In the practical part contains the results of the financial analysis, some of which are subjected to statistical analysis, which analyzes the dependencies between indicators and their development for the next two seasons. The Company is also compared with two competing companies and are given suggestions to improve business perfo
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Saavedra, Pablo da Costa. "Indicadores de insolvência bancária um estudo empírico no Brasil (1994-2004)." Universidade Federal da Bahia, 2008. http://www.adm.ufba.br/sites/default/files/publicacao/arquivo/pablo_da_costa_saavedra.pdf.

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p. 1 - 122<br>Submitted by Santiago Fabio (fabio.ssantiago@hotmail.com) on 2013-01-23T19:50:56Z No. of bitstreams: 1 2222.pdf: 701721 bytes, checksum: 268bf16fcc88888c85b75a1645ec0c99 (MD5)<br>Made available in DSpace on 2013-01-23T19:50:56Z (GMT). No. of bitstreams: 1 2222.pdf: 701721 bytes, checksum: 268bf16fcc88888c85b75a1645ec0c99 (MD5) Previous issue date: 2008<br>A falência de um banco é uma preocupação constante de qualquer órgão de regulação e supervisão internacional. Pelas características particulares do segmento bancário como a exposição ao risco sistêmico e a possibilidade de tra
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Kim, Jung-Hoon. "An analysis of land use change using GIS and spatial analysis a case study of the Seoul metropolitan region perimeter /." Thesis, Online version, 2001. http://ethos.bl.uk/OrderDetails.do?did=1&uin=uk.bl.ethos.369836.

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Greenhoe, Richard J. "Comparison of retention characteristics over time : evidence from the 1992 and 1999 Department of Defense survey of active duty personnel /." Thesis, Monterey, Calif. : Springfield, Va. : Naval Postgraduate School ; Available from National Technical Information Service, 2005. http://library.nps.navy.mil/uhtbin/hyperion/05Mar%5FGreenhoe.pdf.

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Olsson, Jonas. "Tidsdriven ABC-kalkylering inom tredjepartslogistik : Tillämpningar för att driva produktivitet hos PostNord Logistics TPL i Norrköping." Thesis, Linköpings universitet, Logistik- och kvalitetsutveckling, 2017. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-142929.

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PostNord Logistics TPL AB (PostNord) är en av de största aktörerna inom tredjepartslogistik i Norden. Vid däcklagret i Norrköping står PostNord för logistikaktiviteter i samband med inleveranser, lagring, förädling och utleveranser åt flera återförsäljare. Personalkostnader är den överlägset största kostnadsposten och därför fokuserar ledningen på produktivitet, exempelvis genom effektivisering och högre precision vid bemanningsplanering. Studiens syfte var därför att utveckla en kostnadsmodell baserat på tidsdriven ABC-kalkylering för den operativa verksamheten i däcklagret, som kan tillämpas
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Lindström, Agnes, and Frida Persson. "Estimation of Hourly Origin Destination Trip Matrices for a Model of Norrköping." Thesis, Linköpings universitet, Kommunikations- och transportsystem, 2018. http://urn.kb.se/resolve?urn=urn:nbn:se:liu:diva-150135.

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During the last century, the number of car users has increased as an effect of the increasing population growth. To manage the environmental and infrastructural challenges that comes with a more congested traffic network, traffic planning has become of higher importance to analyze the current traffic state and to predict future capacity challenges and effects of investments. These analysis and evaluations are commonly performed in different traffic analysis tools, where updated and realistic traffic demand needs to be provided to ensure reasonable results. In this thesis, a macroscopic model o
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Klar, Robert Günther. "Geographically Weighted Regression based Investigation of Transport Policies for Increased Public Transport Ridership : A Case Study of Stockholm." Thesis, KTH, Transportplanering, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:kth:diva-302708.

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Public transport plays a vital role in society as the economy, the degree of sustainability and the qualityof life of a city is directly affected by transportation. A shift in modal share towards public transport isassociated with many benefits such as increased air quality and improved space allocation within thecity. To further promote public transport, an appropriate measure of competitiveness is required toevaluate the impact of past and future transport policies. This study introduces the journeys per capitaratio as a new way of measuring public transport competitiveness. Firstly, the key
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Books on the topic "Logistics Regression"

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Menard, Scott W. Logistic regression. Sage Publications, 2009.

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Hosmer, David W. Applied Logistic Regression. John Wiley & Sons, Ltd., 2004.

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Stanley, Lemeshow, ed. Applied logistic regression. Wiley, 1989.

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Stanley, Lemeshow, ed. Applied logistic regression. 2nd ed. Wiley, 2000.

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Kleinbaum, David G. Logistic Regression. Springer New York, 1994. http://dx.doi.org/10.1007/978-1-4757-4108-7.

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Kleinbaum, David G., and Mitchel Klein. Logistic Regression. Springer New York, 2010. http://dx.doi.org/10.1007/978-1-4419-1742-3.

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Pampel, Fred. Logistic Regression. SAGE Publications, Inc., 2000. http://dx.doi.org/10.4135/9781412984805.

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Hosmer, David W., and Stanley Lemeshow. Applied Logistic Regression. John Wiley & Sons, Inc., 2000. http://dx.doi.org/10.1002/0471722146.

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Hosmer, David W., Stanley Lemeshow, and Rodney X. Sturdivant. Applied Logistic Regression. John Wiley & Sons, Inc., 2013. http://dx.doi.org/10.1002/9781118548387.

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Hilbe, Joseph. Logistic regression models. Chapman & Hall/CRC, 2009.

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Book chapters on the topic "Logistics Regression"

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Fox, William P., and Rodney X. Sturdivant. "Advanced Regression Models: Nonlinear, Sinusoidal, and Binary Logistics Regression Using R*." In Probability and Statistics for Engineering and the Sciences with Modeling using R. Chapman and Hall/CRC, 2022. http://dx.doi.org/10.1201/9781003317906-14.

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Wang, Yang, and Xiaochun Lu. "Random Forest Regression Model Application for Prediction of China’s Railway Freight Volume." In Collaborative Logistics and Intermodality. Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-50958-3_6.

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Fox, William P., and Jesse Hammond. "Advanced Regression Models: Least Squares, Nonlinear, Poisson and Binary Logistics Regression Using R." In Data Science and Digital Business. Springer International Publishing, 2019. http://dx.doi.org/10.1007/978-3-319-95651-0_12.

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Tiwar, Amit Kr, Umesh Kr Pandey, Anmol Shandilya, Sneha Kesarwani, and Srishti Jaiswal. "Prediction enhancement of logistics regression on mental health dataset." In Intelligent Computing and Communication Techniques. CRC Press, 2025. https://doi.org/10.1201/9781003635680-65.

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Trivedi, Udai Bhan, Milind Bhatt, and Prerna Srivastava. "Prevent Overfitting Problem in Machine Learning: A Case Focus on Linear Regression and Logistics Regression." In Innovations in Information and Communication Technologies (IICT-2020). Springer International Publishing, 2021. http://dx.doi.org/10.1007/978-3-030-66218-9_40.

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Mohan, Tanishka, Gulrej Ahmed, Hemlata Goyal, and Bhupendra Singh Kirar. "Prediction and Analysis of Cardiovascular Disease Using Multivariate Logistics Regression Classification." In Futuristic Trends in Networks and Computing Technologies. Springer Nature Singapore, 2022. http://dx.doi.org/10.1007/978-981-19-5037-7_58.

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Capozza, Claudia, Anatoliy Mokiy, Iryna Zvarych, Olha Ilyash, and Ivan Vankevych. "Financial Challenges and Threats of Circular Economy Logistics." In New Economic Windows. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-64916-5_19.

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AbstractThis chapter explores the economic aspects related to circular economy logistics and highlights the key financial challenges and threats that organizations may face when transitioning to a circular economy business model. We developed a methodological approach for researching financial challenges and threats, which consisted of 4 steps. In the 1st stage of the research, we identified the leader in the trade of processed raw materials—Germany and characterized the factors why this country is the leader. In the next stage, the authors reasonably identified possible financial threats that
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Rioja San Martín, Oscar, and Joaquim Lloveras Maciá. "An Overnight Parcel Logistics Company’s Capillary Distribution Network Design by Regression Analysis." In Annals of Industrial Engineering 2012. Springer London, 2013. http://dx.doi.org/10.1007/978-1-4471-5349-8_20.

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Yao, Li. "Low Carbon Transformation Effect of Logistics Enterprises Based on Adaboost Regression Algorithm." In Lecture Notes in Networks and Systems. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-88287-6_32.

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Kleinbaum, David G. "Introduction to Logistic Regression." In Logistic Regression. Springer New York, 1994. http://dx.doi.org/10.1007/978-1-4757-4108-7_1.

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Conference papers on the topic "Logistics Regression"

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P, Saraswathi, Prabha M, Nega P R, and Santhoshini T S. "Aqua Foresight Logistics Regression Based Rainfall Prediction." In 2024 International Conference on Electrical Electronics and Computing Technologies (ICEECT). IEEE, 2024. http://dx.doi.org/10.1109/iceect61758.2024.10739244.

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Gao, Xiaohan. "Online Education Intelligent Performance Prediction Model Based on Logistics Regression Algorithm." In 2024 International Conference on Artificial Intelligence, Deep Learning and Neural Networks (AIDLNN). IEEE, 2024. https://doi.org/10.1109/aidlnn65358.2024.00038.

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Gong, XiangFei. "Analyzing the Spatial Autocorrelation of Logistics Nodes Using the Geographically Weighted Regression Model." In 2024 3rd International Conference on Smart City Challenges & Outcomes for Urban Transformation (SCOUT). IEEE, 2024. https://doi.org/10.1109/scout64349.2024.00017.

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Malematsa, Phetole A., Giresse M. Komba, and Solly P. Maswikaneng. "An enhanced multifactor authentication using decision-tree and Logistics-Regression machine learning algorithm." In 2024 IEEE 8th Conference on Energy Internet and Energy System Integration (EI2). IEEE, 2024. https://doi.org/10.1109/ei264398.2024.10991855.

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Agarwal, Amit, Stanislav Peceny, Mariana Raykova, Phillipp Schoppmann, and Karn Seth. "Communication-Efficient Secure Logistic Regression." In 2024 IEEE 9th European Symposium on Security and Privacy (EuroS&P). IEEE, 2024. http://dx.doi.org/10.1109/eurosp60621.2024.00031.

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Ceko, Enriko. "On the Relationship between ISO Standards and the Logistic Performance Index." In 9th International Scientific Conference ERAZ - Knowledge Based Sustainable Development. Association of Economists and Managers of the Balkans, Belgrade, Serbia, 2023. http://dx.doi.org/10.31410/eraz.2023.189.

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Using regression analysis, the paper aims to clarify the relationship between trade logistics issues, expressed with the logistic performance index, and quality management, expressed with the ISO standards index. The paper opted for an exploratory study using regression analysis to find relations be­tween the logistics performance index and the ISO standards index, using data complemented Logistic Performance Index, and ISO Standards certificates is­sued worldwide, providing statistical insights into the relations between the LPI and QM, and the ISO Standards Index. It suggests that successful
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Daškevič, Diana, and Aurelija Burinskiene. "Aligning digital transformation with strategic management in logistics." In XXI International May Conference on Strategic Management – IMCSM25 Proceedings, Bor, 30.05.2025. University of Belgrade - Technical Faculty in Bor, Bor, 2024. https://doi.org/10.5937/imcsm25072d.

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Digital transformation plays a vital role in enhancing competitiveness within the logistics sector, yet many organizations struggle to align technological innovation with strategic goals. To address this gap, the study examines how decision making enhances the adoption of digital technologies to strengthen competitive advantage. A five-stage methodology, including case study analysis and expert evaluation, ensures analytical depth and practical relevance. Using a mixed-methods approach, the research integrates qualitative insights from logistics professionals with ordinal logistic regression a
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Fan, Wei, Feng Ding, and Yang Shi. "Parameter Estimation for Hammerstein Nonlinear Controlled Auto-Regression Models." In 2007 IEEE International Conference on Automation and Logistics. IEEE, 2007. http://dx.doi.org/10.1109/ical.2007.4338714.

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Sheldon, John, Ronald Kube, and Hong Zhang. "Oil sand screen modelling using partial least squares regression." In 2008 IEEE International Conference on Automation and Logistics (ICAL). IEEE, 2008. http://dx.doi.org/10.1109/ical.2008.4636679.

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Kaushalya, Chamari, Subachandran Sahana, Omitha Wijenayake, Susith Jayawardana, Navodika Karunarathna, and Naduni Kalansuriya. "Impact of Green Supply Chain Management Practices on Operational Performance in Logistics Companies in Sri Lanka." In Proceedings of the 2nd International Conference on Sustainable & Digital Business. SLIIT Business School, 2023. https://doi.org/10.54389/bodx4217.

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To improve organizational performance and gain a competitive advantage, businesses today realize that environmental sustainability and becoming green are key basic principles. The objective of this study is to investigate how Green Supply Chain Management Practices (GSCMP) would affect the operational performance of logistics companies in Sri Lanka. A questionnaire was used to gather primary data from the sample, which consisted of 152 logistics companies. Statistical Package for Social Sciences (SPSS) software was used to analyze the data using multiple linear regression. According to the stu
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Reports on the topic "Logistics Regression"

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Bai, Z. D., P. R. Krishnaiah, and L. C. Zhao. Variable Selection in Logistic Regression. Defense Technical Information Center, 1987. http://dx.doi.org/10.21236/ada186032.

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BG Amindan and DN Hagedorn. Logistic Regression Applied to Seismic Discrimination. Office of Scientific and Technical Information (OSTI), 1998. http://dx.doi.org/10.2172/1360.

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Graham, Bryan. Sparse Network Asymptotics for Logistic Regression. National Bureau of Economic Research, 2020. http://dx.doi.org/10.3386/w27962.

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Stefanski, L. A., and R. J. Carroll. Covariate Measurement Error in Logistic Regression. Defense Technical Information Center, 1985. http://dx.doi.org/10.21236/ada160277.

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Meloncelli, Daniel. Regression Analysis using SPSS. Instats Inc., 2025. https://doi.org/10.61700/9zohmz8j1gzcj1476.

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This seminar provides a comprehensive introduction to regression analysis using SPSS, equipping researchers with the skills to apply linear and logistic regression techniques in their work. Participants will gain practical experience in model fitting, assumption checking, and interpreting results, enhancing their ability to leverage data effectively in their respective fields.
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Meloncelli, Daniel. Regression Analysis using R. Instats Inc., 2025. https://doi.org/10.61700/j3s1r521de2ee1472.

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This seminar provides a comprehensive introduction to regression analysis using R. Participants will explore the fundamentals of correlation, simple linear regression, multiple regression, and logistic regression. The seminar emphasises practical application, guiding attendees through data preparation, model fitting, assumption checking, and interpretation of results. Hands-on sessions will enable participants to apply regression techniques to real-world datasets, enhancing their analytical skills for research purposes.
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Churchill, Alexandrea, and Grace Kissling. Convergence in Mixed Effects Logistic Regression Models. Journal of Young Investigators, 2019. http://dx.doi.org/10.22186/jyi.36.2.18-35.

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8

Buttrey, Samuel E. The Smarter Regression" Add-In for Linear and Logistic Regression in Excel". Defense Technical Information Center, 2007. http://dx.doi.org/10.21236/ada470645.

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Jakobsen, Tor Georg. Using ChatGPT with Stata: Regression Analysis (Part II). Instats Inc., 2025. https://doi.org/10.61700/2w5b85mmn916t1568.

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Abstract:
This comprehensive 3-day workshop focuses on refining statistical modeling and regression analysis skills by integrating advanced AI tools like ChatGPT with traditional software such as Stata. Participants will gain practical competencies in various regression techniques, including interaction effects (or 'moderation'), logistic regression, missing data, scale construction, transformations, weighting, and how to deal with regression assumptions, along with AI-powered assistance from ChatGPT to clarify concepts and troubleshoot commands.
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Belloni, Alexandre, Victor Chernozhukov, and Ying Wei. Honest confidence regions for a regression parameter in logistic regression with a large number of controls. Institute for Fiscal Studies, 2013. http://dx.doi.org/10.1920/wp.cem.2013.6713.

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