Related references
Note: Only part of the references are listed.
Article
Computer Science, Hardware & Architecture
Mohd Anul Haq
Summary: This research aims to develop an automated weed detection system using machine learning and UAV technology, and achieves high accuracy results.
COMPUTER SYSTEMS SCIENCE AND ENGINEERING
(2022)
Article
Computer Science, Hardware & Architecture
Mohd Anul Haq
Summary: Understanding climatic parameters and water requirements is crucial for adopting sustainable crop practices in a changing climate. The Planetscope constellation of nanosatellites provides high-resolution data that can transform agricultural practices on a large scale. In this study, high-resolution Planetscope data was used to monitor and assess agriculture in the Al-Qassim region of Saudi Arabia. The study utilized the Normalized Difference Vegetation Index (NDVI) to evaluate vegetation pattern changes, and a machine learning-based classification model was used for vegetation classification.
COMPUTER SYSTEMS SCIENCE AND ENGINEERING
(2022)
Article
Energy & Fuels
Fahad Iqbal Syed et al.
Summary: This study presents a smart unconventional EOR performance evaluation tool using intelligent modeling strategies through proxy modeling approach with mechanistic constraints, incorporating physics-based numerical simulation dataset. The tool is well-qualified for forecasting EOR application in unconventional reservoirs with identical characteristics utilizing Deep Neural Network models.
Article
Computer Science, Artificial Intelligence
Yuwen Liu et al.
Summary: The article introduces an attention-based bidirectional gated recurrent unit model for POI category prediction. This method regards users' POI categories as interest preferences, improving the interpretability and prediction accuracy of the model, while simply reflecting user interests.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2022)
Article
Computer Science, Artificial Intelligence
Yuwen Liu et al.
Summary: The study focuses on greenhouse climate prediction, proposing the GCP_lstm model which utilizes LSTM to capture the dependency of climate data. By adding a time sliding window and handling abnormal data, the model shows good robustness in predicting greenhouse climate change for three vegetable types.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2022)
Article
Energy & Fuels
Temoor Muther et al.
Summary: This study presents the application of three new socio-inspired algorithms in hydraulic fracturing optimization and compares them with traditional optimizers. The results demonstrate that multi-CI and TLBO outperform CI, PSO, and GA in determining the optimum fracture design parameters.
JOURNAL OF ENERGY RESOURCES TECHNOLOGY-TRANSACTIONS OF THE ASME
(2022)
Review
Energy & Fuels
Fahad I. Syed et al.
Summary: This article provides a comprehensive literature review on the applications of artificial intelligence (AI) and machine learning (ML) in modeling petrophysical and geomechanical properties. These technologies make it easier, faster, and more accurate to plan and operate reservoir development by learning from experiences in already explored reservoirs. The article also presents systematic counts of publications in this field, reflecting the growing interest in this subject.
Article
Automation & Control Systems
Wenwen Gong et al.
Summary: Integrating lightweight web application programming interfaces (APIs) into mobile Apps is a promising and cost-effective way to quickly develop mobile Apps with desired functions. However, the challenge lies in combining existing web APIs from distinct enterprises or organizations to create compatible and diverse mobile Apps. In order to address this challenge, a novel efficient web APIs recommendation (E-WAR) approach based on locality-sensitive hashing is proposed to recommend desirable web APIs to developers while ensuring privacy protection.
IEEE TRANSACTIONS ON INDUSTRIAL INFORMATICS
(2022)
Article
Computer Science, Information Systems
Mohd Anul Haq
Summary: This study utilizes deep learning to analyze temperature and rainfall changes in the Himalayan states of India and develops models that accurately forecast temperature and rainfall values.
CMC-COMPUTERS MATERIALS & CONTINUA
(2022)
Article
Computer Science, Information Systems
Mohd Anul Haq
Summary: Rapid industrialization and urbanization have worsened ambient air quality, posing high risks to human health and the environment. Previous studies using machine learning and statistical modeling to forecast and classify air pollution have been hindered by the complexity of the data. This study aims to bridge the gap by developing five machine learning models and three forecasting models, incorporating efficient data preprocessing and rigorous optimization. The novel model, SMOTEDNN, achieved the highest accuracy compared to other models.
CMC-COMPUTERS MATERIALS & CONTINUA
(2022)
Article
Energy & Fuels
Fahad I. Syed et al.
Summary: This paper introduces the application of AI and ML in shale gas production performance evaluation, highlighting the enhancement of performance accuracy through data-driven methods, and discusses the utilization of various ML methods.
JOURNAL OF PETROLEUM EXPLORATION AND PRODUCTION TECHNOLOGY
(2021)
Article
Computer Science, Software Engineering
Wenwen Gong et al.
Summary: This article proposes a novel keywords-driven web APIs recommendation approach aiming to provide App developers with functional requirements-compliant and compatible API recommendations. Through a series of experiments, the effectiveness and efficiency of this method have been confirmed compared to existing competitive approaches.
SOFTWARE-PRACTICE & EXPERIENCE
(2021)
Article
Fahad I. Syed et al.
Petroleum Research
(2021)
Article
Environmental Sciences
Mohd Anul Haq
Summary: The study in Al-Qassim region of Saudi Arabia found a decreasing trend in water extraction for irrigation, decreasing trend in annual rainfall, and increasing trend in annual temperature. Vegetation indices showed a good relationship with rainfall and a negative correlation with temperature.
ENVIRONMENTAL TECHNOLOGY
(2021)
Article
Chemistry, Analytical
Mohd Anul Haq et al.
Summary: This study provides a broad overview of changes in patterns of vegetation, snow covers and temperature in Uttarakhand state of India through bulk processing of remotely sensed data. Results show increasing trend of snow-covered areas during pre-monsoon and decreasing vegetation covers during monsoon.
Article
Computer Science, Artificial Intelligence
Yuwen Liu et al.
Summary: With the accumulation of users' check-in data, behavior patterns can be captured to recommend POIs. Due to sparse data, a category-aware GRU model is proposed for better recommendation results.
INTERNATIONAL JOURNAL OF INTELLIGENT SYSTEMS
(2021)
Article
Mohd Anul Haq et al.
Arabian Journal of Geosciences
(2021)
Article
Environmental Sciences
Mohd Anul Haq et al.
NATURAL RESOURCE MODELING
(2020)
Article
Computer Science, Artificial Intelligence
Zahra Karevan et al.
Article
Computer Science, Software Engineering
Isabelle Roesch et al.
COMPUTER GRAPHICS FORUM
(2019)
Article
Multidisciplinary Sciences
Taewook Kim et al.
Article
Thermodynamics
Xiangyun Qing et al.
Article
Chemistry, Analytical
Chiou-Jye Huang et al.
Article
Environmental Sciences
Caihong Hu et al.
Proceedings Paper
Computer Science, Artificial Intelligence
Sheng Chen et al.
2018 2ND INTERNATIONAL CONFERENCE ON ARTIFICIAL INTELLIGENCE APPLICATIONS AND TECHNOLOGIES (AIAAT 2018)
(2018)
