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Articles de revues sur le sujet "And Industry Forecast 2023-2027"

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Muftaydinov, Kiyomidin, and Ilkhomjon Yuldashevich Umarov. "MODELING AND FORECASTING ECONOMIC PROCESSES OF FOOD INDUSTRY ENTERPRISES." Annali d'Italia 61 (November 27, 2024): 31–35. https://doi.org/10.5281/zenodo.14230797.

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Today, for the effective development of the food industry in Uzbekistan, it is important to develop effective economic and managerial decisions and ensure their implementation. The article developed a model of the relationship between the cost of gross production and the depreciation of fixed assets and intangible assets. The ascending order of the case under study is shown by flattening the time series using the least squares method. The dynamics of the wage fund, depreciation of fixed assets and intangible assets in the food industry of the Republic of Uzbekistan in 2014-2023 and foreca
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Sushchenko, Olena, and Oleksii Pohuda. "Analysis of the development factors of the passenger air transport market in the tourism sector." Економіка і регіон/ Economics and region, no. 1(92) (February 9, 2024): 168–73. https://doi.org/10.26906/eir.2024.1(92).3325.

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The article analyses the factors that determine the development of the passenger air transport market. It analyses the dynamics of international tourist arrivals in the regions of the world in 2019-2023 and identifies the busiest routes in the world in 2023. Also, it provides an analysis of the actual and forecast level of global traffic losses and the pace of its recovery. It was determined that according to the optimistic forecast, passenger traffic in 2027 should exceed the level of 2019 by 31%. It was also identified that the impact of global and local events has had a negative impact on b
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SAVCHENKO-BELSKII, K. A., E. I. MANTAEVA, and A. A. MANTSAEVA. "ESTABLISHMENT OF A TOURIST AND RECREATIONAL CLUSTER IN THE REGION: REASONABILITY AND FORECAST." Scientific Works of the Free Economic Society of Russia 239, no. 1 (2023): 180–202. http://dx.doi.org/10.38197/2072-2060-2023-239-1-180-202.

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The article assesses the feasibility of establishing a regional economic cluster. The assessment is tested for the tourism industry. It is based on a two-level classification system of Russian regions and simulation modeling. The classification made it possible to single out typological groups of regions with different industry orientations and to identify groups of different industry development levels. Simulation modeling required studying a number of indicators of the tourism industry and identifying patterns and processes occurring in it in a formalized form. Using built models, the result
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Bylina, Svetlana Gennadievna. "FORECAST ESTIMATES OF LABOR DEMAND IN AGRICULTURE IN RUSSIA." AIC: economics, management, no. 3 (March 1, 2025): 124–34. https://doi.org/10.33305/253-124.

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The influence of the parameters of development of the Russian agricultural sector on the need for workers is studied. Using econometric models, a forecast estimate of the demand for labor in agriculture, forestry, hunting and fishing is made based on the criteria of sectoral development laid down in state program documents: the State Program for the Development of Agriculture and Regulation of Agricultural Products, Raw Materials and Food Markets (State Program), the Strategy for the Development of the Agro-Industrial and Fishing Complexes of the Russian Federation for the Period up to 2030 (S
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HOSSEN, Sayed Mohibul, Mohd Tahir ISMAIL, and Mosab I. TABASH. "THE IMPACT OF SEASONALITY IN TEMPERATURE FORECAST ON TOURIST ARRIVALS IN BANGLADESH: AN EMPIRICAL EVIDENCE." GeoJournal of Tourism and Geosites 34, no. 1 (2021): 20–27. http://dx.doi.org/10.30892/gtg.34103-614.

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In the present study, we aim to investigate how seasonality influences the climate changes on the outdoor thermal comfort for traveling to visit Bangladesh. Wherein, the effect of temperature on tourist arrival is assessed using SANCOVA and SARIMA model at seven attractive sightseeing diverse places in Bangladesh. The highest temperature has appeared in Khulna and Rajshahi with 35.53 °C and 35.85 °C and the lowest temperature was appeared in Rajshahi and Rangamati with 10.40 °C and 11.72 °C, respectively. This result also revealed that the temperature for Dhaka, Chittagong, Cox’s Bazar, Khulna
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XU, QIAN, HUA CHENG, and YABIN YU. "Analysis and forecast of textile industry technology innovation capability in China." Industria Textila 72, no. 02 (2021): 191–97. http://dx.doi.org/10.35530/it.072.02.1759.

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The textile industry of China has been facing with fierce competition and transformational pressures. It is of great significance to study the evolution of textile industry’s technological progress and to predict the trends. The study analyses the technological innovation ability of China’s textile industry based on the data of 270,145 patent applications from 1987 to 2016. At the same time, the Logistic model is used to forecast the technology innovation capability of China’s textile industry. The study found out: the number of Chinese textile patent applications is on a upward trend; enterpr
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Gajdzik, Bożena. "Post-Pandemic Steel Production Scenarios for Poland Based on Forecasts of Annual Steel Production Volume." Management Systems in Production Engineering 31, no. 2 (2023): 172–90. http://dx.doi.org/10.2478/mspe-2023-0019.

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Abstract The paper presents the results of forecasts made for the volume of steel production in Poland based on actual data for the period from 2006 to 2021 with forecasting until 2026. The actual data used for the forecasts included annual steel production volumes in Poland (crude steel) in millions of tons. Basic adaptive methods were used to forecast the volume of steel production for the next five years. When selecting the methods, the course of the trend of the studied phenomenon was taken into account. In order to estimate the level of admissibility of the adopted forecasting methods, as
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Duanaputri, Rohmanita, Sulistyowati Sulistyowati, and Putra Aulia Insani. "Analisis peramalan kebutuhan energi listrik sektor industri di Jawa Timur dengan metode regresi linear." JURNAL ELTEK 20, no. 2 (2022): 50. http://dx.doi.org/10.33795/eltek.v20i2.352.

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Abstrak 
 Pada kehidupan sekarang maupun akan datang, energi listrik menjadi kebutuhan pokok masyarakat. Kebutuhan energi listrik selalu mengalami peningkatan, diikuti meningkatnya pertumbuhan penduduk. Permasalahan akan muncul apabila kebutuhan energi listrik tidak diperkirakan. Maka perlu dilakukan peramalan kebutuhan energi listrik untuk memprediksikan ketersediaan energi listrik di masa mendatang. Pada penelitian ini, dilakukan peramalan kebutuhan energi listrik menggunakan metode regresi linier pada sektor industri di Jawa Timur untuk tahun 2023-2027. Berdasarkan hasil perhitungan pr
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S. Milovanov, Svyatoslav. "Clinical Trials Trends of 2023 Year and Visionary to the Future." International Journal of Clinical Investigation and Case Reports 02, no. 01 (2023): 13–19. http://dx.doi.org/10.55828/ijcicr-21-04.

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Introduction: The importance of studying historical changes in the development of human activity is substantiated by the need to systematize such changes and the possibility of predicting them. Historical changes are extended in time and do not have clear boundaries, requiring greater involvement in their study and the prerequisites for their appearance. Clinical research is more than just the practical application of medical changes and discoveries. They make changes in medical practice but are subject to change. Changes in the clinical research industry are tendentious and develop gradually,
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KUMAR, AJAY, VINAY KUMAR, CHETNA, et al. "Forecasting cotton (Gossypium spp.) prices in major Haryana markets: A time series and ARIMA approach." Indian Journal of Agricultural Sciences 94, no. 9 (2024): 1013–18. http://dx.doi.org/10.56093/ijas.v94i9.150524.

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Economic outputs are an attractive prospect in any field and hence agriculture also relies heavily on economic stability. The costs associated with cotton farming are increasing and profitability is taking a hit in cotton cultivation. Timely and accurate forecast of the price helps the farmers switch between the alternative nearby markets to sale their produce and getting good prices. Present study was carried out during 2022 to 2023 in Haryana to provide some insights into the possible future prices of cotton (Gossypium spp.) with the help of data collected from AGMARKNET and various major co
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Livres sur le sujet "And Industry Forecast 2023-2027"

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Advanced Wound Dressings Market Share, Globe Key Updates, Demand, Size, and Industry Forecast 2023-2027. https://www.fortunebusinessinsights.com/industry-reports/advanced-wound-dressings-market-100384, 2020.

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Biopharmaceutical CMO Market. https://www.fortunebusinessinsights.com/biopharmaceutical-cmo-market-103346, 2020.

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U.S. Genetic Testing Market. https://www.fortunebusinessinsights.com/u-s-genetic-testing-market-105034, 2020.

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Skin Cancer Treatment Market: Skin Cancer Treatment Market Share, Globe Key Updates, Demand, Size, and Industry Forecast 2023-2027. https://www.fortunebusinessinsights.com/skin-cancer-treatment-market-102806, 2020.

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Opioid Use Disorder Market. https://www.fortunebusinessinsights.com/opioid-use-disorder-oud-market-102674, 2020.

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ASEAN Cosmeceuticals Market: ASEAN Cosmeceuticals Market Share, Globe Key Updates, Demand, Size, and Industry Forecast 2023-2028. https://www.fortunebusinessinsights.com/asean-cosmeceuticals-market-106253, 2020.

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Non-hodgkin lymphoma treatment market. https://www.fortunebusinessinsights.com/non-hodgkin-lymphoma-treatment-market-102642, 2020.

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FREEMAN, Frank. Cryptocurrency Market Analysis; Forecast of the Future: Cryptocurrency Investing, a Comprehensive Practical Insight into Bitcoin and Digital Currency Investment From 2023 - 2027. Independently Published, 2022.

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Chapitres de livres sur le sujet "And Industry Forecast 2023-2027"

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Pehin Dato Musa, Siti Fatimahwati, Wardah Hakimah Sumardi, and Rozaidah Idris. "The Halal Pharmaceutical Supply Chain Traceability System: Malaysia, Japan and Brunei Darussalam." In The Halal Industry in Asia. Springer Nature Singapore, 2025. https://doi.org/10.1007/978-981-96-0393-0_19.

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Abstract The production of halal pharmaceuticals in Muslim countries is a growing industry with high market demand. Muslim consumer spending on pharmaceuticals was USD108 billion in 2022 and is forecast to reach USD142 billion in 2027. Due to the growing demand for halal pharmaceuticals, business leaders have begun to respond to the call for halal integrity in medicines and related products in which all ingredients should be permissible to use and consume and be alcohol-free. This chapter examines the use of a traceability system to ensure the halal integrity of pharmaceuticals. A traceability
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Akanmu, Abiola, Adedeji Afolabi, and Akinwale Okunola. "Predicting Mental Workload of Using Exoskeletons for Construction Work: A Deep Learning Approach." In CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality. Firenze University Press, 2023. http://dx.doi.org/10.36253/979-12-215-0289-3.69.

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Exoskeletons are gaining attention as a potential solution for addressing low back injury in the construction industry. However, use of active back-support exoskeletons in construction can trigger unintended consequences which could increase mental workload of users while working with exoskeletons. Prolonged increase in mental workload could impact workers’ wellbeing and productivity. Prediction of mental workload during exoskeleton-use could inform strategies to mitigate the triggers. This study investigates a machine-learning framework for predicting mental workload of workers while using ac
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Akanmu, Abiola, Adedeji Afolabi, and Akinwale Okunola. "Predicting Mental Workload of Using Exoskeletons for Construction Work: A Deep Learning Approach." In CONVR 2023 - Proceedings of the 23rd International Conference on Construction Applications of Virtual Reality. Firenze University Press, 2023. http://dx.doi.org/10.36253/10.36253/979-12-215-0289-3.69.

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Exoskeletons are gaining attention as a potential solution for addressing low back injury in the construction industry. However, use of active back-support exoskeletons in construction can trigger unintended consequences which could increase mental workload of users while working with exoskeletons. Prolonged increase in mental workload could impact workers’ wellbeing and productivity. Prediction of mental workload during exoskeleton-use could inform strategies to mitigate the triggers. This study investigates a machine-learning framework for predicting mental workload of workers while using ac
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Nguyen, Do Minh, Timon Scharmann, and Klaus Dröder. "Material-Adapted Gripping and Handling of PEO-Based Cell Components for All-Solid-State Battery Cell Stacking." In Annals of Scientific Society for Assembly, Handling and Industrial Robotics 2023. Springer Nature Switzerland, 2025. https://doi.org/10.1007/978-3-031-74010-7_10.

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Abstract Lithium-ion batteries (LIBs) immensely contribute to the electromobility’s success for achieving climate change goals. As LIBs are forecasted to succumb to optimization limits in the coming decade, next generation battery technologies, such as all-solid-state batteries (ASSBs), gain noteworthy attention for meeting ever-increasing cell performance requirements. By deploying solid electrolytes (SEs), compared to liquid electrolytes in current LIBs, ASSBs benefit from enhanced safety against flammability and allow for the usage of lithium metal anodes for higher energy densities. Here,
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Heineken-van Dooren, Marierose M. M., and Roy Lindelauf. "Leveraging Data Science for Defence in the Digital Age: Defence AI in the Netherlands." In Contributions to Security and Defence Studies. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-58649-1_10.

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AbstractData science and AI play vital roles in realizing the Dutch Ministry of Defence’s (MoD) vision to work in a “data-driven” manner by 2035. Regarding these technologies, the Dutch MoD prioritizes responsible AI and data science, aiming for technological advancement, information-driven operations, while at the same time becoming a reliable player and advocate in the field of responsible AI. The Dutch MoD holds a human-centric view on AI as a capability multiplier. The Data Science and AI Strategy 2023–2027 emphasizes the importance of high-quality IT, data governance, and ethical decision
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Kathirvel, Naren, Kathirvel Ayyaswamy, and C. Subramanian. "Intelligent Serverless Computing Technology and Recent Trends." In Advances in Computer and Electrical Engineering. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-2869-9.ch002.

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Applications that are serverless can be distributed (many services are connected for smooth operation), elastic (resources can be scaled up and down without limit), stateless (interactions and data aren't stored), event-driven (resources are allocated only when triggered by an event), and hostless (apps aren't hosted on a server). Serverless computing is becoming more and more popular as cloud adoption rises. In many respects, serverless computing unleashes the entire potential of cloud computing. We pay only for the resources consumed, and resources are allocated, increased, or decreased dyna
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Kathirvel, A. "Applications of Serverless Computing." In Advances in Systems Analysis, Software Engineering, and High Performance Computing. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-1682-5.ch014.

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Applications that are serverless can be distributed (many services are connected for smooth operation), elastic (resources can be scaled up and down without limit), stateless (interactions and data aren't stored), event-driven (resources are allocated only when triggered by an event), and hostless (apps aren't hosted on a server). Serverless computing is becoming more and more popular as cloud adoption rises. In many respects, serverless computing unleashes the entire potential of cloud computing. we pay only for the resources consumed, and resources are allocated, increased, or decreased dyna
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Chen, Rurong, Cai Jing, Fu Yingjie, and Wei Ziji. "Comprehensive analysis and forecast of Chinese NEV industry development from 2012 to 2025." In Foresight in Research : Case studies on future issues and methods. Budapesti Gazdasági Egyetem, 2023. http://dx.doi.org/10.29180/9786156342560_6.

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More and more countries are turning to renewable energy to reduce their dependence on traditional fossil fuels as climate change increases. Electric cars have also become a new trend in energy transformation that is strongly supported by many governments. To answer the research questions, we employ a literature review approach and the TOPSIS method based on entropy. This paper begins with a systematic review of the relevant literature to identify key characteristics of the Chinese market for new energy vehicles (NEVs), providing clear theoretical support. Then, the author chose data from 2012
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Kraus, Kateryna, and Nataliia Kraus. "FORECAST OF CAPITAL INVESTMENTS IN THE INDUSTRY OF UKRAINE AND THE PROSPECTS OF POST-WAR RECOVERY OF THE NATIONAL ECONOMY ON THE BASIS OF DIGITAL DEVELOPMENT OF ENTREPRENEURSHIP." In GLOBAL DIGITAL TRENDS AND THEIR IMPACT ON NATIONAL ECONOMIC PROGRESS. OKTAN PRINT, 2024. http://dx.doi.org/10.46489/gdtatione-05-24-29.

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The 21st century was marked by a number of financial, political, socio-economic crises in a number of countries of the world. But despite these challenges and some global turbulence and uncertainty, the innovative development of various sectors of the economy in combination with the digital ‘virus’ is observed in most countries of the world. Ukraine is no exception. Despite the state of war, most sectors of the economy took a course for recovery from the middle of 2023. It is clear to both society and the government that financial and economic improvement in the country, development of digital
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Wang, Yong, Jing Li, Xi Vincent Wang, and Lihui Wang. "Demand Forecasting Study on Cold Chain Logistics of Aquatic Products in Zhejiang Province Based on Gray GM (1, N) Model." In Advances in Transdisciplinary Engineering. IOS Press, 2025. https://doi.org/10.3233/atde250154.

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This paper takes the aquatic products output of Zhejiang Province in 2018–2022 as the original data, constructs 13 relevant forecast indicators by analyzing the influencing factors of cold chain logistics demand, carries out the grey correlation calculation of the indicators, and the results obtained show that there is a strong correlation between these 13 indicators and the cold chain logistics demand of Zhejiang Province. The five indicators with the strongest correlation with the demand for cold chain logistics in Zhejiang Province were selected. The GM (1, 6) model was applied to forecast
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Actes de conférences sur le sujet "And Industry Forecast 2023-2027"

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Kamble, Torana, Madhuri Ghuge, Ronit Rana, Harsh Vardhan, Yash Shelar, and Tushar Machale. "Ensemble Machine Learning Models to Forecast Sales." In 2023 3rd International Conference on Innovative Mechanisms for Industry Applications (ICIMIA). IEEE, 2023. http://dx.doi.org/10.1109/icimia60377.2023.10426565.

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Olonichev, Vasiliy, Boris Staroverov, and Sergey Tarasov. "The Holographic and Perceptron Neuron Networks Joint Application for the Dynamic Systems Behavior Forecast." In 2023 International Russian Smart Industry Conference (SmartIndustryCon). IEEE, 2023. http://dx.doi.org/10.1109/smartindustrycon57312.2023.10110729.

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Zhou, Rong, and JiangXue Di. "Energy Demand Forecast of Hubei Logistics Industry Based on RBF Neural Network." In Proceedings of the 2nd International Conference on Mathematical Statistics and Economic Analysis, MSEA 2023, May 26–28, 2023, Nanjing, China. EAI, 2023. http://dx.doi.org/10.4108/eai.26-5-2023.2334201.

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DiMarco, Steven Francis, Scott M. Glenn, Benjamin Jaimes de la Cruz, et al. "Applications of Adaptive Sampling Strategies of Autonomous Vehicles, Drifters, Floats, and HF-Radar, to Improve Loop Current System Dynamics Forecasts in the Deepwater Gulf of Mexico." In Offshore Technology Conference. OTC, 2023. http://dx.doi.org/10.4043/32459-ms.

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Abstract The Gulf of Mexico holds vital natural, commercial, and societal resources. A diverse array of stakeholders (which includes the offshore energy sector, climate scientists, living resources managers, recreational and commercial fishing industry, tourism, navigation, homeland security, the National Weather Service, oil spill, tropical weather forecasters) rely on accurate and timely prediction of the deepwater dynamics to perform safe operations and to understand the complex interactions of the earth climate and weather system. A strategy to improve predictive skill of numerical ocean c
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Brodetsky, G. L., V. D. Gerami, D. A. Gusev, and A. Yu Zimin. "PROBLEMS OF BALANCE OF EFFICIENCY METRICS OF IMPLEMENTING STRATEGIES FOR DIGITAL TRANSFORMATION OF TRANSPORT AND MANUFACTURING INDUSTRY." In Digital transformation in industry: trends, management, strategies. Institute of Economics of the Ural Brach of Russian Academy of Sciences, 2023. http://dx.doi.org/10.17059/dti-2023-2.

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The article analyzes the effectiveness of the implementation of the Transport Strategy of the Russian Federation until 2030 with a forecast for the period until 2035 and the Strategy for the digital transformation of manufacturing industries in order to achieve their “digital maturity” until 2024 and for the period until 2030. The inconsistency of a number of metrics for the development and digital transformation of these strategies has been revealed, taking into account the differences in the structure of their beneficiaries, as well as the uncertainty that can manifest itself in difficult-to
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Netzell, Pontus, Hussain Kazmi, and Konstantinos Kyprianidis. "Applied Machine Learning for Short-Term Electric Load Forecasting in Cities - A Case Study of Eskilstuna, Sweden." In 64th International Conference of Scandinavian Simulation Society, SIMS 2023 Västerås, Sweden, September 25-28, 2023. Linköping University Electronic Press, 2023. http://dx.doi.org/10.3384/ecp200005.

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With the growing demand, electrification, and renewable proliferation, the necessity of being able to forecast future demand in combination with flexible energy usage is tangible. Distribution network operators often have a power capacity limit agreed with the regional grid, and economic penalties await if crossed. This paper investigates how cities could deal with these issues using data-driven approaches. Hierarchical electric load data is analyzed and modeled using Multiple Linear Regression. Key calendar variables holidays, industry vacation, ”Hour of day” and ”Day of week” are identified
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Mayer, Jan, and Roland Jochem. "Quality forecasts in manufacturing using autoregressive models." In Intelligent Human Systems Integration (IHSI 2023) Integrating People and Intelligent Systems. AHFE International, 2023. http://dx.doi.org/10.54941/ahfe1002848.

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Companies in the manufacturing industry are facing a variety of challenges such as increasing product complexity and variety and the accompanying complexity of production processes. The developments for more sustainability and optimized use of resources are additional societal requirements. Consequently, the demands of efficient solutions in quality management are also increasing. Innovative processes are needed to meet industrial challenges. Therefore, enhanced availability of data in production offers an opportunity. Hence, the combination of associated process and manufacturing knowledge an
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Musora, T., Z. Chazuka, A. Jaison, J. Mapurisa, and J. Kamusha. "Sales Forecasting of Perishable Products: A Case Study of a Perishable Orange Drink." In 10th International Conference on Computer Networks & Communications (CCNET 2023). Academy and Industry Research Collaboration Center (AIRCC), 2023. http://dx.doi.org/10.5121/csit.2023.130408.

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The primary goal of any organization involved in trading business is to maximize profits while keeping costs to a bare minimum. Sales forecasting is an inexpensive way to achieve the aforementioned goal. Sales forecasting frequently leads to improved customer service, lower product returns, lower deadstock, and efficient production planning. Because of short shelf life of food products and importance of product quality, which is of concern to human health, successful sales forecasting systems are critical for the food industry. The ARIMA model is used to forecast sales of a perishable orange d
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Candido, Sílvio, Mohammad-Reza Pendar, and José Carlos Páscoa. "Improving Efficiency of Automotive Coating and Curing Processes Through Deep Learning Algorithms and High-Fidelity CFD Modeling." In ASME 2023 International Mechanical Engineering Congress and Exposition. American Society of Mechanical Engineers, 2023. http://dx.doi.org/10.1115/imece2023-112373.

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Abstract The automobile industry has relied on computational fluid dynamics (CFD) simulations to analyze and optimize the coating and curing processes, speed up product development, and lower the cost of product development. However, CFD modelings of these processes are computationally expensive due to the complexity of the models and the large number of simulations needed, especially when its used complex sprays such as the nithrothermal electrospray. As a result, more efficient methods must be developed to reduce computing time without compromising accuracy. In this article, we analyze how d
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Fernandes, F. B., A. M. B. Braga, A. L. S. Souza, and A. C. Soares. "Geomechanical-Integro-Differential Solution for Biot's Effective Stress-Sensitive Permeability Monitoring During the Well-Reservoir Drawdown." In 57th U.S. Rock Mechanics/Geomechanics Symposium. ARMA, 2023. http://dx.doi.org/10.56952/arma-2023-0019.

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ABSTRACT Incorporating geomechanics to flow models become the mathematical formulation regarding well-test and reservoir engineering more realistic because geomechanical parameters, e.g., in situ and overburden stress, as well as Biot's coefficient, play a fundamental role in pressure response. Hence, permeability stress-sensitive oil reservoirs are the scope of various research in the petroleum industry for minimizing formation damage during drilling, completion, and stimulation operations. This work develops a new analytical solution for the nonlinear hydraulic diffusivity equation (NHDE) wi
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Rapports d'organisations sur le sujet "And Industry Forecast 2023-2027"

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Houston, Robert (RJ), and Brooke Cherfils. South East Queensland Water Safety Strategy 2023-2027. Royal Life Saving - Australia, 2023. http://dx.doi.org/10.62977/84918.

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This drowning prevention Strategy for South East Queensland is the result of a collaborative process involving a range of key community, industry and government stakeholders. Sadly, 366 people have drowned in the region in the last 10 years, each representing the loss of a father, mother, sister brother, child or grandparent with devastating effects on families, friends, health and emergency services workers, and entire communities. This strategy intends to provide the region with guidance for reducing drowning, coordinating collecting action and reinforcing the importance of safe enjoyment of
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O'Connor, Jack, Magdalena Mirwald, Christina Widjaja, Architesh Panda, Jessica Pinheiro, and Soenke Kreft. Technical Report: Uninsurable future. United Nations University - Institute for Environment and Human Security (UNU-EHS), 2023. http://dx.doi.org/10.53324/yodt6712.

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Insurance is a tool for financial risk management used by individuals, organizations, governments and businesses to safeguard themselves against the risk of uncertain financial losses, such as those occurring as a result of damage during an unexpected disaster. However, providing insurance in areas prone to natural hazard events (for example wildfires, droughts, storms, floods) has long been a challenge, and as extreme weather events around the world become more frequent and severe, the increasing cost of the damage they inflict is pushing the industry to breaking point in certain areas. Since
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