Relevant bibliographies by topics / Artificial intelligence AI-Readiness Forest industry

Contents

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

Academic literature on the topic 'Artificial intelligence AI-Readiness Forest industry'

Author: Grafiati
Published: 4 June 2021
Last updated: 27 July 2025

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Journal articles on the topic "Artificial intelligence AI-Readiness Forest industry"

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Orajaka, Amaka V., and Chukwunonso V. Orajaka. "The Role of Artificial Intelligence in Enhancing Supply Chain Performance within Nigeria’s Oil and Gas Sector." International Journal of Research and Innovation in Applied Science X, no. V (2025): 1236–52. https://doi.org/10.51584/ijrias.2025.1005000110.

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This study examines the application of artificial intelligence (AI) in enhancing supply chain performance within Nigeria’s oil and gas sector, with a focus on efficiency, agility, and resilience. As global energy demands and operational complexities rise, the need for digital transformation in supply chain management has become increasingly vital. However, in many developing economies, AI adoption remains limited due to organizational, cultural, and infrastructural barriers. A quantitative research design was employed, using survey data collected from professionals within the Nigerian oil and
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Maithili, Kamble Dr. Shivappa Nagoba* Avinash Swami Nivrutti Kotsulwar Mayur Upade Amrapali Rajput. "Review On Artificial Intelligence Revolutionizing the Pharmaceutical Industry." International Journal of Pharmaceutical Sciences 3, no. 5 (2025): 2028–43. https://doi.org/10.5281/zenodo.15393564.

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Artificial Intelligence (AI) and Machine Learning (ML) are revolutionizing the pharmaceutical industry, driving advancements across drug discovery, formulation, manufacturing, and clinical trials. AI tools such as molecular visualization software, predictive algorithms like Random Forest, and Principal Component Analysis (PCA) are pivotal in assessing drug stability and designing stable drug-polymer systems, which are essential for developing solid dispersions. Artificial Neural Networks (ANNs) have demonstrated superior accuracy in predicting the crystalline and amorphous content of drugs com
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Ooi, Jun Jie, Yit Hong Choo, Andi Prademon Yunus, Wei Hong Lim, and Sui Yang Khoo. "Review on Advancements in Artificial Intelligence and its Applications in Sports." International Journal on Robotics, Automation and Sciences 7, no. 1 (2025): 58–63. https://doi.org/10.33093/ijoras.2025.7.1.7.

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The sport industry is being transformed by Artificial Intelligence (AI) in many ways. This paper seeks to discuss how AI has improved sports science, particularly in boosting the athletes’ performance and avoiding injuries, through various machine learning models like Extreme Gradient Boosting, Support Vector Machines, and Random Forest Regression. These AI tools are more effective than the traditional methods, as they predict the athletes’ performance results more accurately and managing their injuries more proactively. This paper also discusses the challenges of using AI in the sport industr
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Espinel, Ramón, Gricelda Herrera-Franco, José Luis Rivadeneira García, and Paulo Escandón-Panchana. "Artificial Intelligence in Agricultural Mapping: A Review." Agriculture 14, no. 7 (2024): 1071. http://dx.doi.org/10.3390/agriculture14071071.

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Artificial intelligence (AI) plays an essential role in agricultural mapping. It reduces costs and time and increases efficiency in agricultural management activities, which improves the food industry. Agricultural mapping is necessary for resource management and requires technologies for farming challenges. The mapping in agricultural AI applications gives efficiency in mapping and its subsequent use in decision-making. This study analyses AI’s current state in agricultural mapping through bibliometric indicators and a literature review to identify methods, agricultural resources, geomatic to
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Meenakshi Devi Mudunuri, Nagaraju Yalampati, Akshay Kumar Voosala, et al. "Biotechnology and artificial intelligence integration: A concise review of advanced application, advantages and challenges in healthcare." World Journal of Advanced Research and Reviews 24, no. 3 (2024): 2380–88. https://doi.org/10.30574/wjarr.2024.24.3.3761.

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Everyone is talking about artificial intelligence (AI) these days. Unprecedented new potential solutions are made possible when biotechnology and artificial intelligence breakthroughs are coupled. This can support significant Sustainable Development Goals and assist with a number of global issues. Food security, health and well-being sustainable energy, conscientious production and consumption, climate action, and life below water, safeguarding, restoring, and promoting the environmentally friendly forest management and the sustainable utilization of terrestrial ecosystems, preventing desertif
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Meenakshi, Devi Mudunuri, Yalampati Nagaraju, Kumar Voosala Akshay, et al. "Biotechnology and artificial intelligence integration: A concise review of advanced application, advantages and challenges in healthcare." World Journal of Advanced Research and Reviews 24, no. 3 (2024): 2380–88. https://doi.org/10.5281/zenodo.15229477.

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Everyone is talking about artificial intelligence (AI) these days. Unprecedented new potential solutions are made possible when biotechnology and artificial intelligence breakthroughs are coupled. This can support significant Sustainable Development Goals and assist with a number of global issues. Food security, health and well-being sustainable energy, conscientious production and consumption, climate action, and life below water, safeguarding, restoring, and promoting the environmentally friendly forest management and the sustainable utilization of terrestrial ecosystems, preventing desertif
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Li, Jinhui. "The Impact of AI Industry Growth on U.S. AI Sector Stocks: A Machine Learning Analysis." Advances in Economics, Management and Political Sciences 94, no. 1 (2024): 175–86. http://dx.doi.org/10.54254/2754-1169/94/2024ox0203.

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The rapid development of artificial intelligence (AI) since 2020 has significantly impacted the U.S. stock market, necessitating a deeper understanding of its influence on AI-related stocks. This study aims to analyze and predict the returns of the Global X Robotics & Artificial Intelligence ETF (BOTZ) as a proxy for AI industry performance. Employing Random Forest and XGBoost machine learning models, we trained on over a thousand data points to forecast BOTZ ETF returns. Our research reveals that AI-focused stocks and ETFs have outperformed the broader market since 2020, driven by increas
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Suman Kumar Swarnkar. "Integrating Artificial Intelligence and Data Analytics for Supply Chain Optimization in the Pharmaceutical Industry." Journal of Electrical Systems 20, no. 3s (2024): 682–90. http://dx.doi.org/10.52783/jes.1358.

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This inquire about examines the integration of Artificial Intelligence (AI) and information analytics to optimize supply chain forms within the pharmaceutical industry. Through tests and writing audits, the ponder investigates the adequacy of AI calculations counting Linear Regression, Random Forest Regression, K-Means Clustering, and Deep Learning Neural Systems over request estimating, stock optimization, generation planning, and coordination optimization. Results appear that Random Forest Relapse beats Direct Relapse in request determining with RMSE of 80.20, MAE of 60.75, R² of 0.90, and M
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Venu Gopal Avula. "Predictive Intelligence in retail operations: AI-powered forecasting models for demand planning, customer behavior analysis, and supply chain optimization." World Journal of Advanced Engineering Technology and Sciences 4, no. 1 (2021): 106–14. https://doi.org/10.30574/wjaets.2021.4.1.0074.

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The retail industry has undergone significant transformation with the integration of artificial intelligence (AI) and machine learning (ML) technologies. This study presents a comprehensive analysis of AI-powered forecasting models for retail operations, focusing on demand planning, customer behavior analysis, and supply chain optimization. Through the implementation of advanced predictive algorithms including Long Short-Term Memory (LSTM) networks, Random Forest, and XG Boost models, we demonstrate significant improvements in forecasting accuracy. Our findings reveal that AI-driven approaches
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Grace, Camille Curtom, Madhure Nagaraju Sangeetha, Mendonca Eder, Abu-Samaha Mamoun, and Hee Kim Jeong. "Creating an Artificial Intelligence (AI) Model for Healthcare Diagnostics." European Journal of Advances in Engineering and Technology 9, no. 3 (2022): 1–6. https://doi.org/10.5281/zenodo.10643762.

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<strong>ABSTRACT</strong> The US healthcare system is a cottage industry and as it moves toward electronic healthcare data, there is no standard for healthcare interoperability, there is no proper integration among the different clinics and services leading to a lack of continuity and coordination of care with issues concerning data privacy and security. This leads to patients seeking medical services from several clinics to get the most accurate healthcare diagnosis. To solve such problems, we used artificial intelligence (AI) technology more specifically using AI modeling to obtain better an
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Dissertations / Theses on the topic "Artificial intelligence AI-Readiness Forest industry"

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Göransson, Johanna, and Sofi Glas. "AI-READINESS : En kvalitativ fallstudie i skogsindustrin." Thesis, Umeå universitet, Institutionen för informatik, 2021. http://urn.kb.se/resolve?urn=urn:nbn:se:umu:diva-183674.

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Organizations in all industries have reached a transition point because of the rapid development of digital technology. Digitalization and AI has therefore become the driving force for transformation within today's organizations to remain competitive in the digital era. The forest industry is no exception. However, digital transformation through AI within organizations is synonymous with high complexity and the forestry industry faces unique challenges to overcome because of the industry's traditional approach and the corporate culture that comes with it. This approach creates challenges for t
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Books on the topic "Artificial intelligence AI-Readiness Forest industry"

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Lauterbach, Anastassia, and Andrea Bonime-Blanc. The Artificial Intelligence Imperative. ABC-CLIO, LLC, 2018. http://dx.doi.org/10.5040/9798400614835.

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This practical guide to artificial intelligence and its impact on industry dispels common myths and calls for cross-sector, collaborative leadership for the responsible design and embedding of AI in the daily work of businesses and oversight by boards. Artificial intelligence has arrived, and it's coming to a business near you. The disruptive impact of AI on the global economy—from health care to energy, financial services to agriculture, and defense to media—is enormous. Technology literacy is a must for traditional businesses, their boards, policy makers, and governance professionals. This i
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Book chapters on the topic "Artificial intelligence AI-Readiness Forest industry"

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Jażdżewski, Tomasz, Krzysztof Regulski, Adam Bułka, Pawel Malara, Adrian Czeszkiewicz, and Marcin Trajer. "Information Extraction from Time Series in the EDM Drilling Process." In Lecture Notes in Mechanical Engineering. Springer International Publishing, 2024. http://dx.doi.org/10.1007/978-3-031-58006-2_12.

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AbstractElectrical discharge machining (EDM) allows to obtain small holes with the high efficiency and high quality. Such features are most common in jet engine turbine airfoils. The main problem of the analysis is detection of a moment when the machine should stop the drilling process—the breakthrough detection. Machine learning applications requires that data and models to be prepared by specialists that can extract the most important information from an input data and choose most suitable Artificial Intelligence (AI) algorithm for particular case. This Article describes an experiment on how
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Tsuchiya, Motohiro. "Overcoming the Long Shadow of the Past: Defense AI in Japan." In Contributions to Security and Defence Studies. Springer Nature Switzerland, 2024. http://dx.doi.org/10.1007/978-3-031-58649-1_22.

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AbstractSince the end of World War II, Japan has not had a full-fledged military, but only Self-Defense Forces (SDF) for the sole purpose of “exclusively defensive defense.” Hesitancy exists in society, especially in academia, to research and develop technologies that could be diverted to military use. This has created a long shadow of the past in which public opinion, strategic culture, and the academic-industrial ecosystem mutually reinforce each other not to directly address defense technologies, though Japan is often recognized as one of the most technologically advanced countries. However
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Kumar, Chunchu Suchith, D. P. Divya Vani, K. Damodar, Geetha Manoharan, and Nagendram Veerapaga. "Climate Change Mitigation Through AI Solutions." In Advances in Hospitality, Tourism, and the Services Industry. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-4135-3.ch003.

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Climate change endangers humanity. Global warming impacts everyone. Globally, people are working on climate change mitigation and scientific and technological solutions, regardless of their development level. AI will greatly impact climate change mitigation. Artificial intelligence data analysis predicts weather, manages energy, and analyzes industrial pollution. Blockchain AI improves sustainability efficiency, traceability, and transparency. The AI-driven supply management system for climate change mitigation optimizes and simplifies supply chains. To reduce carbon emissions and production a
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Gunjal, Rahul Dnyanesh, and Dr Sheetal Sonawdekar. "FUTURE TRENDS OF AI IN FOOD SCIENCE & TECHNOLOGY AND AGRICULTURE." In Futuristic Trends in Agriculture Engineering & Food Sciences Volume 3 Book 13. Iterative International Publisher, Selfypage Developers Pvt Ltd, 2024. http://dx.doi.org/10.58532/v3bcag13p1ch14.

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Artificial Intelligence (AI) falls under the domain of computer science and aims to replicate human cognitive processes, learning abilities, and knowledge retention. AI can be categorized into strong AI and weak AI. Weak AI focuses on creating machines that imitate human intelligence and judgment, while strong AI asserts that machines can replicate human thought processes. A variety of sectors, including gaming, weather prediction, heavy industry, process industry, food production, medicine, data analysis, stem cell research, and knowledge representation, have adopted AI techniques for their s
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Kathirvel, A., and A. K. Naren. "Diabetes and Pre-Diabetes Prediction by AI Using Tuned XGB Classifier." In Medical Robotics and AI-Assisted Diagnostics for a High-Tech Healthcare Industry. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-2105-8.ch004.

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The great majority of diabetes patients in India provide a unique set of challenges, and the prospective availability of data may significantly present a unique opportunity for efficiently addressing these challenges. If all doctors use electronic medical records to obtain this data, India may have a great chance to become a leader in this field of study. In this endeavor, the necessary electronic devices are routinely used to collect patient data. Artificial intelligence would help identify upcoming problems and perhaps even assist in developing solutions that are especially geared to make de
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Gon, Anudeepa, Sudipta Hazra, Siddhartha Chatterjee, and Anup Kumar Ghosh. "Application of Machine Learning Algorithms for Automatic Detection of Risk in Heart Disease." In Cognitive Cardiac Rehabilitation Using IoT and AI Tools. IGI Global, 2023. http://dx.doi.org/10.4018/978-1-6684-7561-4.ch012.

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The main cause of death worldwide is heart disease, emphasizing the need for accurate risk prediction models to recognise those who are at high risk. In this study, we propose an automated approach using artificial intelligence to forecast the likelihood of developing heart disease. The dataset consists of various clinical and demographic features, including blood pressure, cholesterol levels, age, gender, and exercise habits. We evaluate the performance of numerous machine learning algorithms, such as neural networks, logistic regression, support vector machines, and random forests, in predic
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Asbaş, Caner, and Şule Erdem Tuzlukaya. "The New Agricultural Revolution." In Generating Entrepreneurial Ideas With AI. IGI Global, 2024. http://dx.doi.org/10.4018/979-8-3693-3498-0.ch012.

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Artificial intelligence constitutes one of the hottest topics in terms of new technological paradigms today. On the other side, agriculture, forestry, and fishery sectors play a key role for humanity since people's food are produced and needs of various sectors including medicine, textile, furniture and construction are met with the activities in these areas. In this context, it was inevitable that artificial intelligence has been integrated into these areas to enhance the efficiency, effectiveness, optimization, and fertility of agriculture, forestry and fishery activities, similar to previou
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"AI in Industry." In Understanding the Role of Artificial Intelligence and Its Future Social Impact. IGI Global, 2021. http://dx.doi.org/10.4018/978-1-7998-4607-9.ch005.

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The past two years have seen a tremendous number of changes in the global AI landscape. There has been a stable balance with the US as the unquestioned leader in the global IT market for nearly the past 20 years and by extension the international AI industry as well, which has evolved from the data science and big data analysis sector to become the engine of the 4th industrial revolution, global economic growth, and social progress that it is today. However, when it comes to AI spending, the US is outgunned by China whose government is investing $150 billion to support its goal to become the u
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Tariq, Muhammad Usman. "The Role of AI in Transforming Hospitality Operations-Enhancing Efficiency and Guest Experience." In Smart Operations and Enhancing Guest Experience in the Hospitality Industry. IGI Global, 2025. https://doi.org/10.4018/979-8-3373-2145-5.ch016.

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Integrating artificial intelligence (AI) into hospitality operations has revolutionized the industry by increasing efficiency, optimizing resource management, and improving guest experience. AI-driven solutions like chatbots, virtual concierges, and intelligent spatial technology have automated customer service to provide seamless interaction and personalized experiences. Advanced data analytics and machine learning enable dynamic pricing, forecast forecasts, and demand forecasts. It allows you to maximize your hotel, maximize sales, and streamline operations. AI-controlled security measures,
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Mongkol, Kulachet. "The Future of Artificial Intelligence in Southeast Asia." In Handbook of Research on Artificial Intelligence and Knowledge Management in Asia’s Digital Economy. IGI Global, 2022. http://dx.doi.org/10.4018/978-1-6684-5849-5.ch002.

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Thailand's robotics and artificial intelligence (AI) skills are increasing quickly as a result of its relevance to global supply chains and the improvements pushed by the coronavirus outbreak and global megatrends. The Thai government has incorporated AI into its National Development Plan, and the Thailand 4.0 national policy pays a lot of attention to AI, robotics, and digital industries. Since AI has a significant influence on digital transactions and Thailand's economic growth, the Thai government must foresee future advancements, particularly in the AI industry, in order to respond effecti
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Conference papers on the topic "Artificial intelligence AI-Readiness Forest industry"

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Kochkina, Nataliia, Iryna Andriushchenko, and Gianluca Gatto. "Strategic AI Adoption: Economic Impact, Case Studies from Handy.ai, and Industry Readiness." In 2024 IEEE International Conference on Artificial Intelligence & Green Energy (ICAIGE). IEEE, 2024. https://doi.org/10.1109/icaige62696.2024.10776631.

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Antsiferova, V., and E. Golova. "APPLICATION OF ARTIFICIAL INTELLIGENCE FOR THE FORESTRY COMPLEX." In ENERGY-SAVING AND ENVIRONMENTALLY SAFE TECHNOLOGIES OF THE TIMBER INDUSTRY – 2025. FSBE Institution of Higher Education Voronezh State University of Forestry and Technologies named after G.F. Morozov, 2025. https://doi.org/10.58168/e-sestti2025_164-170.

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The article examines the impact of artificial intelligence on forestry, as well as the future of digital technologies used in the forest industry. Despite the traditional conservatism of the forestry sector, AI technologies are beginning to be actively used to solve problems that previously required human participation, such as illegal logging and satellite monitoring. AI demonstrates high efficiency in analyzing space images, which allows for more accurate detection of changes in forest resources. However, experts emphasize that AI will not be able to completely replace humans in monitoring,
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Alkhawaher, A., H. Al Jishi, and S. Al-Aseef. "Advanced ESP Monitoring System for Performance and Production Optimization." In SPE Middle East Artificial Lift Conference and Exhibition. SPE, 2024. http://dx.doi.org/10.2118/221543-ms.

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Abstract This paper outlines the design, development, and implementation of an upgraded Variable Speed Drive (VSD) system integrated with Artificial Intelligence (AI) for Electrical Submersible Pumps (ESP). The upgrade aims to enhance real-time monitoring of reservoir fluid properties, specifically Specific Gravity (SG), to optimize ESP performance and reduce operational costs. Importantly, this system is designed to ensure effective long-term well management, providing a sustainable solution for the industry. After evaluating various machine learning models, the integration of the Random Fore
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Hazra, Sandip, and Arkadip Amitava Khan. "Application of AI/ML in Hydrobush Tuning to Enhance Overall Value Proposition." In Noise & Vibration Conference & Exhibition. SAE International, 2025. https://doi.org/10.4271/2025-01-0132.

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&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;In the highly competitive automotive industry, optimizing vehicle components for superior performance and customer satisfaction is paramount. Hydrobushes play an integral role within vehicle suspension systems by absorbing vibrations and improving ride comfort. However, the traditional methods for tuning these components are time-consuming and heavily reliant on extensive empirical testing. This paper explores the advancing field of artificial intelligence (AI) and machine learning (ML) in the hydrobush tuning process, u
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Shekhawat, Dushyant Singh, Vishal Devgun, Bhartendu Bhatt, et al. "Well Intervention Opportunity Management Using Artificial Intelligence and Machine Learning." In ADIPEC. SPE, 2022. http://dx.doi.org/10.2118/211824-ms.

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Abstract Operators face many challenges when selecting well-intervention candidates and evaluating a field’s potential because the process is highly time consuming, labor intensive, and susceptible to cognitive biases. An operator can lose up to USD 10 million/year because of ineffective well-intervention strategies in a single field. The objective of this study is to reduce such losses and standardize the well-intervention process by intelligently using the domain knowledge with artificial-intelligence (AI) and machine-learning (ML) techniques. The workflow developed in this study can automat
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Agbaji, Armstrong Lee. "Developing Next Generation Petrotechnical Professionals in the Age of AI." In Abu Dhabi International Petroleum Exhibition & Conference. SPE, 2021. http://dx.doi.org/10.2118/207813-ms.

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Abstract The most common challenge facing the oil industry in the Age of AI is talent scarcity. As digital transformation continues to redefine what it takes to work in the industry, staying relevant in the industry will require knowledge and understanding of the underlying technologies driving this transformation. It also requires a re-evaluation of how next generation petrotechnical professionals are nurtured, educated, and trained. The human talent that is needed in the Age of AI is different, and simply obtaining a science or engineering degree will no longer suffice to survive and thrive
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Vashist, Devendra, Rishi Raj, and Deepanshu Sharma. "Artificial Intelligence in Electric Vehicle Battery Management System: A Technique for Better Energy Storage." In SAENIS TTTMS Thermal Management Systems Conference. SAE International, 2024. http://dx.doi.org/10.4271/2024-28-0089.

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&lt;div class="section abstract"&gt;&lt;div class="htmlview paragraph"&gt;The automobile industry is currently undergoing a huge transition from IC Engine based systems to electric based mobility systems. Battery technology based on Li ion has made interesting move towards popularization of electric vehicles (EVs) in world market. battery management system (BMS) forms one of the major constituents of this technology. Battery pack as a whole is the most sought-after component of EVs which needs intensive monitoring and control. Battery parameters such as State of Health (SOH) and State of Charg
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Alkhawaher, A., H. Al Jishi, and S. Al-Aseef. "Advanced ESP Monitoring System for Performance and Production Optimization." In Offshore Technology Conference. OTC, 2025. https://doi.org/10.4043/35532-ms.

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Abstract This paper outlines the design, development, and implementation of an upgraded Variable Speed Drive (VSD) system integrated with Artificial Intelligence (AI) for Electrical Submersible Pumps (ESP). The upgrade aims to enhance real-time monitoring of reservoir fluid properties, specifically Specific Gravity (SG), to optimize ESP performance and reduce operational costs. Importantly, this system is designed to ensure effective long-term well management, providing a sustainable solution for the industry. After evaluating various machine learning models, the integration of the Random Fore
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Adeeyo, Yisa. "Random Forest Ensemble Model for Reservoir Fluid Property Prediction." In SPE Nigeria Annual International Conference and Exhibition. SPE, 2022. http://dx.doi.org/10.2118/212044-ms.

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Abstract Reservoir fluid PVT properties are measured in the laboratory for various use in reservoir engineering evaluation and estimation. Despite the indispensability of these PVT parameters, PVT lab data are seldomly available and if available may be unreliable. Instead, various empirical models have been developed and used in the industry. These empirical models are inherently inaccurate when used to predict PVT properties of fluid from different geological region with different depositional environment and fingerprint. Artificial Intelligence (AI) has evolved over the years and provided so
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Saad, Amal, and Alifiya Zohair. "Getting Practical About the Future of Work a Framework for Upskilling and Reskilling Based on Trends Impacting the Oil and Gas Industry." In ADIPEC. SPE, 2023. http://dx.doi.org/10.2118/216540-ms.

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Abstract The FoW is a forecast of how work, workers, and workplaces will evolve in the upcoming years (SHRM, 2022). According to McKinsey, by 2030, up to 30 to 40 percent of all workers in developed countries may need to move to new occupations or upgrade their skills significantly with the impact of Digitalization and Artificial Intelligence AI (Hancock, B., et. Al. 2020). For some organizations, the future of work is exciting. For most, it creates anxiety. Studies indicate variation in readiness for the future based on country, gender (LHH, 2022), and even generation (Chambers, N., 2019). Wh
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Reports on the topic "Artificial intelligence AI-Readiness Forest industry"

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Quimba, Francis Mark, Neil Irwin Moreno, and Alliah Mae Salazar. Readiness for AI Adoption of Philippine Business and Industry: The Government's Role in Fostering Innovation- and AI-Driven Industrial Development. Philippine Institute for Development Studies, 2024. https://doi.org/10.62986/dp2024.35.

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This paper examines the current state of artificial intelligence (AI) adoption in Philippine businesses and industries, analyzing the barriers to adoption and evaluating the government's role in fostering AI-driven industrial development. Through an analysis of various AI readiness indices and case studies, the research finds that while basic digital infrastructure is widespread, with 90.8 percent of establishments having computers and 81 percent having internet access, advanced technology adoption remains limited. Only 14.9 percent of firms use AI technologies, with adoption concentrated in u
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Quimba, Francis Mark, Ramonette Serafica, Connie Bayudan-Dacuycuy, Abigail Andrada, and Neil Irwin Moreno. Green and Digital: Managing the Twin Transition toward Sustainable Development. Philippine Institute for Development Studies, 2023. http://dx.doi.org/10.62986/dp2023.21.

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The global shift toward sustainability and increased digitalization is evident. Nations are integrating renewable energy, carbon emission reduction, and advancements in green technologies into their development plans. Simultaneously, Industry 4.0 has revealed the diverse ways technology influences human life. Rather than separate factors, these dual forces are interconnected elements that countries must navigate for sustainable progress. As countries pursue development strategies, taking a closer look at this twin phenomenon is important. This study assesses how investments, labor, science, te
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Ampatzidis, Yiannis, Mahendra Bhandari, Andres Ferreyra, et al. AI in Agriculture: Opportunities, Challenges, and Recommendations. Chair Alex Thomasson. Council for Agricultural Science and Technology, 2025. https://doi.org/10.62300/iaag042514.

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Artificial Intelligence (AI) is rapidly being integrated into people’s lives, reshaping industries, and enabling previously unimagined innovation, even in agriculture. Generative AI focuses on creating content like text and pictures based on vast quantities of data. ExtensionBot is a generative AI platform that supports agricultural extension by providing farmers with accurate scientific information and specific recommendations. It has been shown to deliver more accurate responses to agricultural questions than broader generative AI models. Other forms of AI have been used to analyze data to p
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