Ananthakrishnan Balasundaram^1,2, Ayesha Shaik^1,2,*, Japmann Kaur Banga², Aman Kumar Singh²

CMC-Computers, Materials & Continua, Vol.79, No.1, pp. 779-799, 2024, DOI:10.32604/cmc.2024.048362

Abstract Industrial activities, through the human-induced release of Green House Gas (GHG) emissions, have been identified as the primary cause of global warming. Accurate and quantitative monitoring of these emissions is essential for a comprehensive understanding of their impact on the Earth’s climate and for effectively enforcing emission regulations at a large scale. This work examines the feasibility of detecting and quantifying industrial smoke plumes using freely accessible geo-satellite imagery. The existing system has so many lagging factors such as limitations in accuracy, robustness, and efficiency and these factors hinder the effectiveness in supporting timely response to industrial fires. In this… More >

Salem Alhayani^*, Diane R. Murphy

CMC-Computers, Materials & Continua, Vol.76, No.2, pp. 2235-2259, 2023, DOI:10.32604/cmc.2023.038003

Abstract The Internet service provider (ISP) is the heart of any country’s Internet infrastructure and plays an important role in connecting to the World Wide Web. Internet exchange point (IXP) allows the interconnection of two or more separate network infrastructures. All Internet traffic entering a country should pass through its IXP. Thus, it is an ideal location for performing malicious traffic analysis. Distributed denial of service (DDoS) attacks are becoming a more serious daily threat. Malicious actors in DDoS attacks control numerous infected machines known as botnets. Botnets are used to send numerous fake requests to overwhelm the resources of victims… More >

Qing Wang^*, Haige Wang, Hongchun Huang, Lubin Zhuo, Guodong Ji

FDMP-Fluid Dynamics & Materials Processing, Vol.19, No.10, pp. 2569-2578, 2023, DOI:10.32604/fdmp.2023.025349

Abstract Sticking is the most serious cause of failure in complex drilling operations. In the present work a novel “early warning” method based on an artificial intelligence algorithm is proposed to overcome some of the known problems associated with existing sticking-identification technologies. The method is tested against a practical case study (Southern Sichuan shale gas drilling operations). It is shown that the twelve sets of sticking fault diagnostic results obtained from a simulation are all consistent with the actual downhole state; furthermore, the results from four groups of verification samples are also consistent with the actual downhole state. This shows that… More >

Yuhan Liu, Yuqiao Zheng^*, Zhuang Ma, Cang Wu

Energy Engineering, Vol.120, No.5, pp. 1223-1237, 2023, DOI:10.32604/ee.2023.026329

Abstract An operating condition recognition approach of wind turbine spindle is proposed based on supervisory control and data acquisition (SCADA) normal data drive. Firstly, the SCADA raw data of wind turbine under full working conditions are cleaned and feature extracted. Then the spindle speed is employed as the output parameter, and the single and combined normal behavior model of the wind turbine spindle is constructed sequentially with the pre-processed data, with the evaluation indexes selected as the optimal model. Finally, calculating the spindle operation status index according to the sliding window principle, ascertaining the threshold value for identifying the abnormal spindle… More >

Wen Deng¹, Guangjun Liang^1,2,3,*, Chenfei Yu¹, Kefan Yao¹, Chengrui Wang¹, Xuan Zhang¹

CMC-Computers, Materials & Continua, Vol.75, No.1, pp. 1561-1576, 2023, DOI:10.32604/cmc.2023.035016

Abstract With the frequent occurrence of telecommunications and network fraud crimes in recent years, new frauds have emerged one after another which has caused huge losses to the people. However, due to the lack of an effective preventive mechanism, the police are often in a passive position. Using technologies such as web crawlers, feature engineering, deep learning, and artificial intelligence, this paper proposes a user portrait fraud warning scheme based on Weibo public data. First, we perform preliminary screening and cleaning based on the keyword “defrauded” to obtain valid fraudulent user Identity Documents (IDs). The basic information and account information of… More >

Zizhen Qin, Yuxin Liu, Tianze Zhang^*

Journal on Artificial Intelligence, Vol.4, No.3, pp. 143-154, 2022, DOI:10.32604/jai.2022.031843

Abstract With the rapid development of interest rate market and big data, the banking industry has shown the obvious phenomenon of “two or eight law”, 20% of the high quality customers occupy most of the bank’s assets, how to prevent the loss of bank credit card customers has become a growing concern for banks. Therefore, it is particularly important to establish a customer churn early warning model. In this paper, we will use the random forest method to establish a customer churn early warning model, focusing on the churn of bank credit card customers and predicting the possibility of future churn… More >

Yonghui Duan¹, Keqing Zhao^1,*, Yibin Guo², Xiang Wang²

Computer Systems Science and Engineering, Vol.45, No.2, pp. 2207-2222, 2023, DOI:10.32604/csse.2023.032297

Abstract A number of risks exist in commercial housing, and it is critical for the government, the real estate industry, and consumers to establish an objective early warning indicator system for commercial housing risks and to conduct research regarding its measurement and early warning. In this paper, we examine the commodity housing market and construct a risk index for the commodity housing market at three levels: market level, the real estate industry and the national economy. Using the Bootstrap aggregating-grey wolf optimizer-support vector machine (Bagging-GWO-SVM) model after synthesizing the risk index by applying the CRITIC objective weighting method, the commercial housing… More >

Zhengyu Wu¹, Kaiqiang Li¹, Lin Yuan², Jingcheng Zhang¹, Xianfeng Zhou^1,*, Dongmei Chen^1,*, Kaihua Wei¹

Phyton-International Journal of Experimental Botany, Vol.91, No.10, pp. 2269-2282, 2022, DOI:10.32604/phyton.2022.022607

Abstract As the source and main producing area of tea in the world, China has formed unique tea culture, and achieved remarkable economic benefits. However, frequent meteorological disasters, particularly low temperature frost damage in late spring has seriously threatened the growth status of tea trees and caused quality and yield reduction of tea industry. Thus, timely and accurate early warning of frost damage occurrence in specific tea garden is very important for tea plantation management and economic values. Aiming at the problems existing in current meteorological disaster forecasting methods, such as difficulty in obtaining massive meteorological data, large amount of calculation… More >

Saeed Ahmed^1,2, Noor Gul^1,3, Jahangir Khan⁴, Junsu Kim¹, Su Min Kim^1,*

CMC-Computers, Materials & Continua, Vol.71, No.3, pp. 5061-5082, 2022, DOI:10.32604/cmc.2022.023639

Abstract Flash floods are deemed the most fatal and disastrous natural hazards globally due to their prompt onset that requires a short prime time for emergency response. Cognitive Internet of things (CIoT) technologies including inherent characteristics of cognitive radio (CR) are potential candidates to develop a monitoring and early warning system (MEWS) that helps in efficiently utilizing the short response time to save lives during flash floods. However, most CIoT devices are battery-limited and thus, it reduces the lifetime of the MEWS. To tackle these problems, we propose a CIoT-based MEWS to slash the fatalities of flash floods. To extend the… More >

Shaleeza Sohail¹, Atif Alvi^2,*, Aasia Khanum³

CMC-Computers, Materials & Continua, Vol.71, No.2, pp. 3211-3225, 2022, DOI:10.32604/cmc.2022.023560

Abstract Major issues currently restricting the use of learning analytics are the lack of interpretability and adaptability of the machine learning models used in this domain. Interpretability makes it easy for the stakeholders to understand the working of these models and adaptability makes it easy to use the same model for multiple cohorts and courses in educational institutions. Recently, some models in learning analytics are constructed with the consideration of interpretability but their interpretability is not quantified. However, adaptability is not specifically considered in this domain. This paper presents a new framework based on hybrid statistical fuzzy theory to overcome these… More >