Electricity production based forecasting of greenhouse gas emissions in Turkey with deep learning, support vector machine and artificial neural network algorithms

Journal of Cleaner Production, Journal Year: 2020, Volume and Issue: 285, P. 125324 - 125324

Published: Dec. 1, 2020

Language: Английский

---

Assessment for crop water stress with infrared thermal imagery in precision agriculture: A review and future prospects for deep learning applications

Computers and Electronics in Agriculture, Journal Year: 2021, Volume and Issue: 182, P. 106019 - 106019

Published: Feb. 9, 2021

Language: Английский

---

Forecasting of future greenhouse gas emission trajectory for India using energy and economic indexes with various metaheuristic algorithms

Journal of Cleaner Production, Journal Year: 2022, Volume and Issue: 360, P. 131946 - 131946

Published: April 29, 2022

Language: Английский

---

A mini-review of machine learning in big data analytics: Applications, challenges, and prospects

Big Data Mining and Analytics, Journal Year: 2022, Volume and Issue: 5(2), P. 81 - 97

Published: Jan. 24, 2022

The availability of digital technology in the hands every citizenry worldwide makes an available unprecedented massive amount data. capability to process these gigantic amounts data real-time with Big Data Analytics (BDA) tools and Machine Learning (ML) algorithms carries many paybacks. However, high number free BDA tools, platforms, mining it challenging select appropriate one for right task. This paper presents a comprehensive mini-literature review ML BDA, using keyword search; total 1512 published articles was identified. were screened 140 based on study proposed novel taxonomy. outcome shows that deep neural networks (15%), support vector machines artificial (14%), decision trees (12%), ensemble learning techniques (11%) are widely applied BDA. related applications fields, challenges, most importantly openings future research, detailed.

Language: Английский

---

A Review of Climate-Smart Agriculture: Recent Advancements, Challenges, and Future Directions

Sustainability, Journal Year: 2023, Volume and Issue: 15(4), P. 3404 - 3404

Published: Feb. 13, 2023

Global climate change has posed serious threats to agricultural production. Reducing greenhouse gas (GHG) emissions and ensuring food security are considered the greatest challenges in this century. Climate-smart agriculture (CSA) is a concept that can provide solution development faces. It do so sustainable way by increasing adaptability, decreasing GHG emissions, national security. So far, little research systematically reviewed progresses CSA developing developed countries. A review on recent advancements, challenges, future directions of will be quite timely valuable. In paper, definition goals identified. Then, advancements countries reviewed. The existing problems analyzed pointed out. Finally, proposals prospects for proposed. Using advanced internet technology ensure information security, improvement cropping patterns, management techniques, carrying out “internet + weather” service improving quality service, conducting weather index-based insurance as main direction CSA. This provides new ideas strategies strengthening ecological environmental protection, promoting green development, mitigating change.

Language: Английский

---

Sustainable AI-based production agriculture: Exploring AI applications and implications in agricultural practices

Smart Agricultural Technology, Journal Year: 2024, Volume and Issue: 7, P. 100416 - 100416

Published: Feb. 17, 2024

In general, agriculture plays a crucial role in human survival as primary source of food, alongside other sources such fishing. Unfortunately, global warming and environmental issues, particularly less privileged nations, hamper the Agricultural sector. It is estimated that range 720 to 811 million individuals experienced food insecurity. Today's faced significant difficulties obstacles, do surveillance monitoring systems (climate, energy, water, fields, works, cost, fertilizers, diseases, etc.). The COVID-19 pandemic has exacerbated susceptibilities insufficiencies inherent worldwide systems. Current agricultural practices tend prioritize productivity profitability over conservation long-term sustainability. To establish sustainable capable meeting needs projected ten billion people next 30 years, substantial structural automation changes are required. However, these obstacles can be overcome by employing smart technologies advancing Artificial Intelligence (AI) operations. AI believed contribute sustainability goals multiple sectors, incorporation renewable energy. anticipated will revitalize both existing new fields retrofitting, installing integrating automatic devices instruments. This paper presents comprehensive review most promising novel applications industry. Furthermore, transition precision investigated.

Language: Английский

---

Prediction modelling framework comparative analysis of dissolved oxygen concentration variations using support vector regression coupled with multiple feature engineering and optimization methods: A case study in China

Ecological Indicators, Journal Year: 2023, Volume and Issue: 146, P. 109845 - 109845

Published: Jan. 2, 2023

Dissolved oxygen (DO) is an essential indicator for assessing water quality and managing aquatic environments, but it still a challenging topic to accurately understand predict the spatiotemporal variation of DO concentrations under complex effects different environmental factors. In this study, practical prediction framework was proposed based on support vector regression (SVR) model coupling multiple intelligence techniques (i.e., four data denoising techniques, three feature selection rules, hyperparameter optimization methods). The holistic tested using matrix (17,532 observation in total) 12 indicators from vital monitoring stations longest inter-basin diversion project world Middle-Route South-to-North Water Diversion Project China), during year 2017 2020 period. results showed that we advocated could successfully concentration variations geographical locations. used "wavelet analysis–LASSO regression–random search–SVR" combination Waihuanhe station has best performance, with Root Mean Square Error (RMSE), (MSE), Absolute (MAE), coefficient determination (R2) values 0.251, 0.063, 0.190, 0.911, respectively. combined methods can significantly promote robustness accuracy provide new universal way investigating understanding drivers variations. For management department, comprehensive also identify reveal key parameters should be concerned monitored factors change. More studies terms potential integrated risk multi-indicators mega projects and/or similar bodies are required future.

Language: Английский

---

Artificial intelligence-based decision support systems in smart agriculture: Bibliometric analysis for operational insights and future directions

Frontiers in Sustainable Food Systems, Journal Year: 2023, Volume and Issue: 6

Published: Jan. 9, 2023

As the world population is expected to touch 9.73 billion by 2050, according Food and Agriculture Organization (FAO), demand for agricultural needs increasing proportionately. Smart replacing conventional farming systems, employing advanced technologies such as Internet of Things (IoT), Artificial Intelligence (AI), Machine Learning (ML) ensure higher productivity precise agriculture management overcome food demand. In recent years, there has been an increased interest in researchers within Agriculture. Previous literature reviews have also conducted similar bibliometric analyses; however, a lack research Operations Research (OR) insights into This paper conducts Bibliometric Analysis past work OR knowledge which done over last two decades 4.0, understand trends gaps. Biblioshiny, data mining tool, was used conducting analysis on total number 1,305 articles collected from Scopus database between years 2000–2022. Researchers decision makers will be able visualize how newer theories are being applied they can contribute toward some gaps highlighted this review paper. While governments policymakers benefit through understanding Unmanned Aerial Vehicles (UAV) robotic units farms optimize resource allocation. Nations that arid climate conditions would informed satellite imagery mapping assist them detecting irrigation lands their scarce resources.

Language: Английский

---

Estimation methods of wetland carbon sink and factors influencing wetland carbon cycle: a review

Carbon Research, Journal Year: 2024, Volume and Issue: 3(1)

Published: May 20, 2024

Abstract In the global ecosystem, wetlands are vital carbon sinks, playing a crucial role in absorbing greenhouse gases such as dioxide and mitigating warming. Accurate estimation of wetland content is essential for research on sinks. However, cycle complex, sinking affected by climate, topography, water level conditions, vegetation types, soil other factors. This has caused significant challenges current studies, most focused impact individual factors often ignoring interaction between various factors, which further leads to uncertainty measurements. paper aims elucidate process cycle, summarize affecting explore interplay their influence aiming provide theoretical support study Additionally, this reviews advantages disadvantages measurement methods, proposes directions combining machine learning identifies existing difficulties measurement, offers suggestions serve reference future sink management. Graphical

Language: Английский

---

Catalyzing net-zero carbon strategies: Enhancing CO2 flux Prediction from underground coal fires using optimized machine learning models

Journal of Cleaner Production, Journal Year: 2024, Volume and Issue: 441, P. 141043 - 141043

Published: Jan. 31, 2024

Language: Английский

---