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Review
Environmental Sciences
M. Awais et al.
Summary: Water management is crucial for sustainable agriculture, especially in semi-arid regions. Remote sensing technologies, such as UAVs, have the potential to improve irrigation by providing real-time environmental data. UAV remote sensing can track crop fields and assess water status, enhancing water stress management in irrigation.
INTERNATIONAL JOURNAL OF ENVIRONMENTAL SCIENCE AND TECHNOLOGY
(2023)
Article
Operations Research & Management Science
Umair Waqas et al.
Summary: Supply chain risk management is crucial for the survival and growth of agropreneurs. This study reveals the mediating effect of supply chain risk management in reducing the impact of supply chain risks and increasing supply chain performance among small scale agropreneurs in Malaysia. It also highlights the moderating role of knowledge management in the relationship between supply chain risks and supply chain risk management.
ANNALS OF OPERATIONS RESEARCH
(2023)
Article
Computer Science, Information Systems
Anusha Vangala et al.
Summary: Agricultural industry, being a vital contributor to the economy, has witnessed significant changes in its operation with the advancement of precision farming and IoT. This paper explores the security scenarios in husbandry and proposes an architecture for smart farming. It conducts a literature survey on security protocols and authentication protocols in smart agriculture, as well as studies the current progress in IoT-based tools and systems.
CLUSTER COMPUTING-THE JOURNAL OF NETWORKS SOFTWARE TOOLS AND APPLICATIONS
(2023)
Article
Mathematics, Interdisciplinary Applications
Yu Feng et al.
Summary: Every enterprise in the supply chain will participate in managing the supply chain, and their decisions will impact other members and themselves. Due to different interests, there are trade-offs in the multi-supply chain between the upstream and downstream. With increasing competition and cooperation, game theory is widely used to analyze competition and collaboration among enterprises, combining game theory and auction theory. However, issues such as the number of iterations and potential for local monopoly exist in double auctions. To address this, the GGPSO algorithm is introduced to improve the double auctions mechanism and achieve global optimization of the supply chain.
FRACTALS-COMPLEX GEOMETRY PATTERNS AND SCALING IN NATURE AND SOCIETY
(2023)
Article
Computer Science, Information Systems
M. Chithambarathanu et al.
Summary: The most important elements in the realm of commercial food standards are effective pest management and control. Crop pests can have a significant impact on crop quality and productivity. It is crucial to develop new tools for diagnosing pest diseases before they cause major crop losses. In this survey, recent research in the field of crop pest and pathogen identification using machine learning techniques and deep learning methods was presented, aiming to increase crop productivity while providing the highest level of protection.
MULTIMEDIA TOOLS AND APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
Manas Kumar Mohanty et al.
Summary: An efficient machine learning-based framework is proposed for crop price prediction to assist farmers in estimating profit and loss in advance. The framework consists of four functional blocks: crop yield prediction, determination of supply, demand prediction, and crop price prediction. Various time series-based algorithms are utilized to forecast crop yield, while the supply is determined using predicted yield, residue, and import values. The demand is predicted solely based on the year, and crop price is predicted using different approaches including time series, statistical methods, and machine learning techniques. The decision tree regressor is identified as the best model for predicting crop price in this work, showing the superiority of the proposed framework over existing approaches.
NEURAL COMPUTING & APPLICATIONS
(2023)
Editorial Material
Computer Science, Artificial Intelligence
Nian Zhang et al.
NEURAL COMPUTING & APPLICATIONS
(2023)
Article
Computer Science, Artificial Intelligence
A. Pavithra et al.
Summary: Plant phenotyping and Precision agriculture face specific challenges and demands for plant disease detection and diagnosis. Precision agriculture involves managing crop factors based on spatial and temporal variability within a field. Automatic disease detection and classification systems are being explored to improve plant production and reduce crop losses. This article presents a new Deep Learning-based Automated Plant Disease Detection and Classification Model that focuses on leaf and fruit regions for precision agriculture.
Article
Computer Science, Artificial Intelligence
Dekera Kenneth Kwaghtyo et al.
Summary: This article provides a comprehensive survey of existing smart farming models for precision agriculture, focusing on machine learning approaches and innovations in predicting and optimizing agricultural practices. The article highlights the poor performance of certain models due to issues with the dataset used and negligence in the pre-processing and feature extraction stages. It demonstrates how machine learning can automate agricultural practices, enhance crop quantity and quality, and reduce human labor. The challenges and prospects of smart farming models are also outlined for further exploration by researchers.
ARTIFICIAL INTELLIGENCE REVIEW
(2023)
Article
Operations Research & Management Science
Yael Perlman et al.
Summary: This study analyzes a dual-channel supply chain model with two suppliers offering organic and conventional agricultural products. The research considers heterogeneity in consumer valuations and product value depreciation. Through analytical and numerical analysis, the study reveals the pricing relationships and profit conditions among the supply chain members.
ANNALS OF OPERATIONS RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
Jingyang Wang et al.
Summary: This paper proposes a new gate control unit (NGCU) based on recurrent neural networks (RNN) for high-precision prediction of time series data. NGCU outperforms traditional methods in terms of prediction accuracy and training time.
Article
Computer Science, Artificial Intelligence
Miaomiao Ji et al.
Summary: The NPI serves as a key statistical indicator for evaluating the agricultural products wholesale market in China, and the DA-RNN model is introduced in this work to better predict NPI using average prices of major agricultural products. Experimental results show that the DA-RNN model outperforms other deep learning methods in terms of various evaluation metrics.
PROGRESS IN ARTIFICIAL INTELLIGENCE
(2022)
Article
Economics
Yingli Wu et al.
Summary: This study explores risk assessment methods for agricultural supply chain finance using genetic algorithms and neural networks, which have been shown to effectively reduce credit risks in agricultural SCF through case analysis validation.
COMPUTATIONAL ECONOMICS
(2022)
Article
Computer Science, Artificial Intelligence
Shengting Wu et al.
Summary: This paper proposes a stock price prediction method S_I_LSTM that combines multiple data sources and investor sentiment using sentiment analysis and convolutional neural network, as well as long short-term memory network for predicting the China Shanghai A-share market. Experimental results show that the method outperforms traditional methods on real data sets of five listed companies.
CONNECTION SCIENCE
(2022)
Article
Telecommunications
P. Vinothiyalakshmi et al.
Summary: Cloud computing is a rapidly growing technology where resource allocation poses challenges. This paper proposes using auction-based technique for resource allocation to reduce complexity and meet customer and provider expectations, with experimental results showing higher efficiency of the proposed algorithm.
WIRELESS PERSONAL COMMUNICATIONS
(2022)
Article
Telecommunications
Shubhashish Goswami et al.
Summary: The use of deep-learning methods in big-data research has revitalized the decision-making process in the business and enterprise sectors, enhancing the efficiency of data processing.
WIRELESS PERSONAL COMMUNICATIONS
(2022)
Article
Management
Ming Luo et al.
Summary: This paper examines the impact of temperature control on the freshness and profitability of fresh agricultural products. By constructing a dynamic game model and discussing different decision-making mechanisms, it highlights the importance of consumer preferences in the supply chain. The research findings indicate that temperature control investments and consumer preferences can increase profits by improving market demand and integrating the supply chain.
OPERATIONS MANAGEMENT RESEARCH
(2022)
Article
Computer Science, Theory & Methods
Ziyi Sun et al.
Summary: This paper integrates genetic algorithm and particle swarm algorithm to optimize the BP neural network, and establishes a housing price prediction model based on mixed genetic particle swarm BP neural network. Through training and simulation prediction, the model's validity and accuracy are proved. The paper also predicts the average price of residential commercial housing in Chongqing in 2021, providing a reference for government macro-control and sellers.
INTERNATIONAL JOURNAL OF FOUNDATIONS OF COMPUTER SCIENCE
(2022)
Review
Computer Science, Artificial Intelligence
Subir Kumar Chakraborty et al.
Summary: With the challenges of shrinking natural resources and climate change, deep learning offers immense possibilities in improving agricultural outputs and addressing global food security concerns. It has been successfully applied in various aspects of agricultural engineering, such as soil moisture estimation, disease detection, and agro-produce quality evaluation.
NEURAL COMPUTING & APPLICATIONS
(2022)
Article
Management
Archana A. Mukherjee et al.
Summary: Blockchain technology is conceptualized as a disruptive technology in today's Industry 4.0 context. Its features such as smart contracts, decentralization, transparency, and privacy protection make it suitable for complex and multi-level supply chains, improving sustainability and agility. The high desirability index of blockchain-enabled supply chain over traditional supply chain justifies its application for sustainable supply chain management.
OPERATIONS MANAGEMENT RESEARCH
(2022)
Article
Computer Science, Artificial Intelligence
Pradeep Hewage et al.
Summary: This article introduces a novel lightweight data-driven weather forecasting model, which outperforms traditional models in weather prediction performance by comparing various machine learning methods, statistical forecasting methods, dynamic ensemble methods, and NWP models.
PATTERN ANALYSIS AND APPLICATIONS
(2021)
Article
Multidisciplinary Sciences
Mohsen Shahhosseini et al.
Summary: The study shows that adding simulated crop model variables to machine learning models can reduce prediction errors and that variables related to soil moisture have the biggest impact on predictions. It indicates that more hydrological inputs are needed for improved accuracy in yield predictions.
SCIENTIFIC REPORTS
(2021)
Article
Computer Science, Information Systems
Yao Xia et al.
Summary: The study introduces a service composition auction mechanism based on user preferences, which dynamically determines service prices and ensures strategic-proofness. Experimental results demonstrate that the auction mechanism not only meets desirable properties, but also helps users find satisfactory service composition schemes.
FRONTIERS OF INFORMATION TECHNOLOGY & ELECTRONIC ENGINEERING
(2021)
Article
Social Sciences, Mathematical Methods
Prilly Oktoviany et al.
Summary: The paper presents a two-step hybrid model based on machine learning methods for valuing derivatives on agricultural commodities. It assigns historical prices to different price states using K-means clustering and predicts future price states based on external factors. The model generates price scenarios via Monte Carlo simulation and compares them with existing models using error measures.
DECISIONS IN ECONOMICS AND FINANCE
(2021)
Article
Economics
Myeong Jun Kim et al.
Summary: This study revisited the time-varying Okun's law using US data and found that the number of working hours and utilization are important factors affecting the fluctuations of the Okun's coefficients. The long-term fluctuations of the estimated time-varying Okun's coefficient have a similar pattern to the detrended real GDP series. The regression estimates were also shown to be stable with respect to the considered EEMD method through a simple simulation.
EMPIRICAL ECONOMICS
(2021)
Article
Operations Research & Management Science
Ilkyeong Moon et al.
OPERATIONAL RESEARCH
(2020)
Article
Computer Science, Information Systems
Yeong-Seok Seo et al.
HUMAN-CENTRIC COMPUTING AND INFORMATION SCIENCES
(2020)
Article
Operations Research & Management Science
Bo Yan et al.
OPERATIONAL RESEARCH
(2019)
Article
Automation & Control Systems
Zhenni Li et al.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2019)
Article
Engineering, Manufacturing
Zhao-Hui Liu et al.
ADVANCES IN MANUFACTURING
(2019)
Article
Engineering, Electrical & Electronic
Chaojie Wang et al.
CIRCUITS SYSTEMS AND SIGNAL PROCESSING
(2018)
Article
Operations Research & Management Science
Quyen Ho
OPTIMIZATION LETTERS
(2017)
Review
Chemistry, Multidisciplinary
Vineet Kumar et al.
ENVIRONMENTAL CHEMISTRY LETTERS
(2017)
Article
Information Science & Library Science
Bo Yan et al.
INFORMATION TECHNOLOGY & MANAGEMENT
(2015)
