Article
Environmental Studies
Shucen Jiao, Yan Zhang, Yuxin Xiao, Xiang Li, Meicheng Li
Summary: Carbon quota assets have become increasingly important in power generation companies, and evaluating their value is crucial for sustainable development. This study proposes a method for evaluating carbon quota assets using the Lasso-Back Propagation Neural Network model. It considers the impact of company operations on the value of carbon quota assets and introduces intelligent algorithms to improve accuracy. By valuing carbon quota assets in the secondary market, power generation companies can optimize their carbon assets management.
ENVIRONMENTAL IMPACT ASSESSMENT REVIEW
(2023)
Article
Computer Science, Artificial Intelligence
Assem Badr
Summary: In order to achieve faster machine learning, this research proposes a new BP rule called ILR-ML. ILR-ML introduces the concept of Learning Ratio and performs the full BP algorithm with 100% accuracy per each learning iteration, making it more suitable for online machine learning.
NEURAL COMPUTING & APPLICATIONS
(2021)
Article
Construction & Building Technology
Patrick Arnaud Wandji Zoumb, Xiaozhen Li
Summary: Forecasting the behavior of the train-bridge system under strong waves is crucial for designing cross-sea bridges. This study investigates the influence of earthquake-induced hydrodynamic force on the stochastic responses of the train-bridge interaction using a surrogate model called back-propagation neural network. The results show that the earthquake-induced hydrodynamic force significantly affects the train-bridge system, and the choice of peak period minimizes this effect.
ADVANCES IN STRUCTURAL ENGINEERING
(2022)
Article
Mathematics, Applied
Ren Liu, Xiaoqun Zhang
Summary: Deep neural network (DNN) has gained significant attention in various applications, and the effectiveness of DNN heavily relies on network training algorithms. Although stochastic gradient descent (SGD) and other explicit gradient-based methods are commonly used, they face challenges such as gradient vanishing and explosion when training complex and deep neural networks. In this paper, a semi-implicit backpropagation method is proposed, which combines the ideas of error backpropagation (BP) and proximal point methods (PPM), to overcome these challenges and improve performance in terms of loss decreasing and accuracy.
JOURNAL OF NONLINEAR AND VARIATIONAL ANALYSIS
(2023)
Article
Environmental Sciences
Zhaohui Xiong, Xiaogong Sun, Jizhang Sang, Xiaomin Wei
Summary: In this study, three machine learning methods were used to calibrate MODIS PWV in 2019, at annual and monthly timescales. The results show that the RF method performs best at the annual timescale, while the GRNN method performs best at the monthly timescale. The spatial and temporal variation patterns of the RMS values are significantly weakened after the modeling by machine learning methods.
Article
Environmental Sciences
Kangle Liu, Tao Lin, Tingting Zhong, Xinran Ge, Fuchun Jiang, Xue Zhang
Summary: Monitoring THMs levels in water supply systems is crucial for ensuring drinking water safety, but it is time-consuming. This study explored the feasibility of using neural network models (BPNN, GABP, GRNN) to predict THMs occurrence. The results showed that GRNN had the best prediction performance, although the accuracy for BDCM prediction was not high. Accurate predictions by GRNN made THMs monitoring in real water supply systems possible and practical.
SCIENCE OF THE TOTAL ENVIRONMENT
(2023)
Article
Engineering, Mechanical
Fucheng Deng, Ziqiang Deng, He Liang, Lihua Wang, Haitao Hu, Yi Xu
Summary: In this study, the erosion rate of slotted screen was calculated using the CFD method, and a prediction model for erosion life was established based on BP neural network. The study found that the screen erosion was influenced by kinematic viscosity and particle diameter with turning points, and the predicted model showed good agreement with the actual conditions.
ENGINEERING FAILURE ANALYSIS
(2021)
Article
Construction & Building Technology
Patrick Arnaud Wandji Zoumb, Xiaozhen Li
Summary: This study investigates the influence of earthquake-induced hydrodynamic force on the stochastic responses of the train-bridge interaction using the Newmark-beta method. The results show that the earthquake-induced hydrodynamic force involves significant responses of the train-bridge system.
ADVANCES IN STRUCTURAL ENGINEERING
(2022)
Article
Engineering, Electrical & Electronic
Ruichao Zhu, Jiafu Wang, Yajuan Han, Sai Sui, Tianshuo Qiu, Yuxiang Jia, Mingde Feng, Xiaofeng Wang, Lin Zheng, Shaobo Qu
Summary: This article proposes a design method for aperture-multiplexing metasurfaces using back-propagation neural network (BPNN) to achieve independent wave-front modulation for orthogonally-polarized waves. A modified Jerusalem Cross (MJC) structure is proposed as the metasurface unit cell to decouple orthogonal interactions. A dictionary mapping between reflection phase and structural parameters of MJC is established using BPNN to facilitate metasurface design. The feasibility of this method is verified by demonstrating a focusing metasurface for both x- and y-polarized waves simultaneously.
IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION
(2022)
Article
Mathematics, Interdisciplinary Applications
Hao Zhang, Jia-Hui Mu
Summary: This study proposes a replenishment decision model based on back propagation neural network multivariate regression analysis, which can accurately predict the replenishment quantity in pharmacies. By applying this model in intelligent pharmacies, it can effectively prevent overstocking or shortage of inventory, thereby improving financial situation.
Article
Engineering, Environmental
Angelika Hess, Eberhard Morgenroth
Summary: The study found that both adsorption and biodegradation play important roles in BAC filters, with biodegradation being the dominant mechanism in the upper part of the filter and sorption capacity buffering high influent TOC concentrations in the lower part. The generous filter design with low average filtration rates ensures long-term TOC removal, with backwashing required only after more than 800 days of operation.
Article
Engineering, Electrical & Electronic
S. Poorani, P. Balasubramanie
Summary: The study introduces a deep learning-based automated mechanism (ABPN) to improve the accuracy of seizure detection from EEG signals. Verified results show that the ABPN system performs the best among various parameters, with sensitivity, specificity, and accuracy reaching 96.32%, 95.12%, and 98.36% respectively.
CIRCUITS SYSTEMS AND SIGNAL PROCESSING
(2021)
Article
Environmental Sciences
Ziyan Liu, Ling Han, Ming Liu
Summary: Global warming caused by greenhouse gas emissions has resulted in unprecedented extreme weather events, posing significant threats to human life and sustainable development. China, as the largest emitter of CO2 in the world, has pledged to reach carbon emission peak by 2030. However, estimating county-level carbon emissions in China is challenging due to a lack of statistical data.
ENVIRONMENTAL SCIENCE AND POLLUTION RESEARCH
(2023)
Article
Multidisciplinary Sciences
Hongwei Bai, Qianqian Cao, Subang An
Summary: This paper proposes a prediction model and algorithm for the clock bias of the BP neural network based on the optimization of the mind evolutionary algorithm (MEA), which is used to optimize the initial weights and thresholds of the BP neural network. The accuracy of the comparison between clock bias data is verified with and without one-time difference processing. The results demonstrate that the MEA-BP model has good stability in predicting the accuracy of satellite clock bias.
SCIENTIFIC REPORTS
(2023)
Article
Computer Science, Information Systems
Kunming Zheng, Qiuju Zhang, Li Peng, Shuisheng Zeng
Summary: This study proposes an adaptive memetic differential evolution-back propagation-fuzzy neural network (AMDE-BP-FNN) control method for efficient and precise control of robots with complex dynamic characteristics, while reducing control costs.
INFORMATION SCIENCES
(2023)
Article
Environmental Sciences
Muqiu Hu, Xin Zhao, Jinghan Gu, Lulu Qian, Zhiqing Wang, Yuanyuan Nie, Xiaoyu Han, Long An, Haiqiang Jiang
Summary: Due to its simple process, environmental friendliness, and low operating costs, biometallurgy has become a popular technology for metals recovering from low-grade ores and tailings. An optimized agar was used to isolate and grow functional bacteria, resulting in the successful isolation of six functional stains. These strains were further tested for their ability to leach metals from polymetallic sulfide tailings, with significant improvements observed when the strains were mixed together. The selection of leaching process should be based on tailings composition and target metals.
ENVIRONMENTAL RESEARCH
(2024)
Review
Environmental Sciences
Saqib Hassan, Aswin Thacharodi, Anshu Priya, R. Meenatchi, Thanushree A. Hegde, R. Thangamani, Ht Nguyen, Arivalagan Pugazhendhi
Summary: An Endocrine Disrupting Chemical (EDC) is a compound that disrupts the function of the endocrine system and is found in the environment. EDCs, such as Bisphenol A and pesticides, have been shown to have negative effects on the female reproductive system. Understanding the relationship between EDCs and women's health is crucial for developing strategies to protect reproductive health and informing public policy decisions.
ENVIRONMENTAL RESEARCH
(2024)
Article
Environmental Sciences
Lichang Zhou, Zhaoling Li, Boyi Cheng, Jinqi Jiang, Xinqi Bi, Zongping Wang, Guanghao Chen, Gang Guo
Summary: Thiosulfate can promote sulfur-mediated bacterial activity, inhibit glycogen accumulating organisms, and enhance denitrification efficiency. After the carbon source is reduced, the competitive ability of glycogen accumulating organisms increases, resulting in reduced sulfate reduction.
ENVIRONMENTAL RESEARCH
(2024)
Article
Environmental Sciences
Claire E. Campbell, Devyn L. Cotter, Katherine L. Bottenhorn, Elisabeth Burnor, Hedyeh Ahmadi, W. James Gauderman, Carlos Cardenas-Iniguez, Daniel Hackman, Rob McConnell, Kiros Berhane, Joel Schwartz, Jiu-Chiuan Chen, Megan M. Herting
Summary: Recent studies have found a connection between air pollution and increased risk for behavioral problems during development. However, more longitudinal studies are needed to investigate how exposure during the transition to adolescence may affect emotional behaviors.
ENVIRONMENTAL RESEARCH
(2024)
Article
Environmental Sciences
Jing-hong Liang, Ru-yu Yang, Mei-ling Liu, Ying-qi Pu, Wen-wen Bao, Yu Zhao, Li-xin Hu, Yu-shan Zhang, Shan Huang, Nan Jiang, Xue-ya Pu, Shao-yi Huang, Guang-hui Dong, Ya-jun Chen
Summary: This study examines the association between urban Green and blue spaces (GBS) exposure and Emotion and behavior problems (EBP) in youth populations. The findings suggest that higher exposure to GBS, particularly green spaces (GS) and blue spaces (BS), is associated with a decrease in the risk of developing total difficulties in young individuals. The joint effect of GS and BS may also contribute to the decrease in EBPs.
ENVIRONMENTAL RESEARCH
(2024)
Article
Environmental Sciences
Diego Ruiz-Sobremazas, Mario Ruiz Coca, Miguel Morales-Navas, Rocio Rodulfo-Cardenas, Caridad Lopez-Granero, Maria Teresa Colomina, Cristian Perez-Fernandez, Fernando Sanchez-Santed
Summary: Air pollution is associated with a range of health issues and gestational exposure to environmental pollutants may be linked to neurodevelopmental disorders. This study investigated the effects of oral gestational exposure to particulate matter (PM) on ultrasonic vocalizations (USV). The findings suggest that this exposure may lead to social deficits and abnormal gene expression related to neurotransmitter systems. Further research is needed to better understand the effects of air pollution on neurodevelopmental disorders and the neurotransmission systems involved.
ENVIRONMENTAL RESEARCH
(2024)
Article
Environmental Sciences
Yagmur Kabakci, Sadiye Kosar, Ozgur Dogan, Fehmi Gorkem Uctug, Osman Atilla Arikan
Summary: This study investigated the effect of electrohydrolysis pretreatment on municipal solid waste. The results showed that applying electrohydrolysis pretreatment increased methane production and reduced the time required for hydrolysis, suggesting it is a promising method to improve anaerobic digestion efficiency.
ENVIRONMENTAL RESEARCH
(2024)
Article
Environmental Sciences
Chuanwu Zhao, Yaozhong Pan, Hanyi Wu, Yu Zhu
Summary: This study analyzed the impact of industrial zones on urban heat islands using remote sensing images and a novel spectral index. The research found that the contraction or expansion of industrial zones has a significant effect on land surface temperature. The results are valuable for environmental assessment and fine management of industrial cities.
ENVIRONMENTAL RESEARCH
(2024)
Article
Environmental Sciences
Bang Du, Zhongzhong Wang, Piet N. L. Lens, Xinmin Zhan, Guangxue Wu
Summary: This study investigated the performance, syntrophic relationships, microbial communities, and metabolic pathways of ethanol-fed reactors with different operational modes and solids retention times. The results showed that different microorganisms were enriched under different SRT conditions, and syntrophic bacteria related to methane production could be enriched under low SRT conditions.
ENVIRONMENTAL RESEARCH
(2024)
Article
Environmental Sciences
Gokulan Ravindiran, Sivarethinamohan Rajamanickam, Muralikrishnan Ramalingam, Gasim Hayder, Balamurugan Karupaiya Sathaiah, Madhava Krishna Reddy Gaddam, Senthil Kumar Muniasamy, Priya Arunkumar
Summary: The present study investigated the sustainable approach for wastewater treatment using waste algal blooms. The biochar produced by the marine algae Ulva reticulata was used to remove chromium, nickel, and zinc from aqueous solutions. The study examined the adsorbents' properties and stability using SEM/EDX, FTIR, and XRD. The results showed that the biochar had high removal efficiency for the toxic metals, and the packed bed column effectively removed the heavy metal ions. The Thomas and Adams-Bohart models were found to best fit the regression values, and desorption studies were conducted to understand the sorption and elution processes.
ENVIRONMENTAL RESEARCH
(2024)
Review
Environmental Sciences
Vignesh Vinayagam, Kavitha Nagarasampatti Palani, Sudha Ganesh, Siddharth Rajesh, Vedha Varshini Akula, Ramapriyan Avoodaiappan, Omkar Singh Kushwaha, Arivalagan Pugazhendhi
Summary: The presence of pollutants in water contributes to global pollution and poses significant threats to humans and wildlife. Finding effective wastewater treatment techniques is crucial for reducing pollutant accumulation in the environment. This paper highlights recent advances in the electrochemical advanced oxidation method and other processes for treating pharmaceuticals, dyes, and pesticide-polluted effluents.
ENVIRONMENTAL RESEARCH
(2024)
Article
Environmental Sciences
M. M. M. Ahmed, Kai-Yue Chen, Fang-Yu Tsao, Yi-Cheng Hsieh, Yu-Ting Liu, Min Tzou
Summary: This study investigated the sorption of citric acid onto humic acid-iron hydr(o)xide coprecipitate (HAFHCP) and the reciprocal effects of citric acid and P sorption on HAFHCP. The results showed that citric acid could increase P availability and have an impact on P sorption.
ENVIRONMENTAL RESEARCH
(2024)
Article
Environmental Sciences
Xibo Xu, Zeqiang Wang, Xiaoning Song, Wenjie Zhan, Shuting Yang
Summary: The selection of predictor variables is crucial in building a digital mapping model for potentially toxic elements (PTEs) in soil. Traditionally, spatial and spectral parameters have been used as predictor variables, but the temporal dimension is often overlooked. This study demonstrates the value of incorporating temporal indices in the model, leading to significant performance improvements. The temporal-spatial-spectral covariate combinations used in a random forest (RF) algorithm achieve satisfactory mapping accuracy and outperform other methods.
ENVIRONMENTAL RESEARCH
(2024)
Article
Environmental Sciences
Yan Pei, Xun Liu, Mengbo Cao, Zijun Wang, Hongbing Yang
Summary: Heteroatom doping can reconfigure the electronic structure of heterogeneous catalysts, leading to the development of advanced oxidation water purification materials with superior performance and stability. In this study, a series of catalysts with different elemental doping were prepared using a simple and environmentally friendly method. The S-doped NiCo2O4 catalyst showed excellent catalytic performance for the removal of Tetracycline, with significantly increased kinetic constant and high oxidation and mineralization efficiency in a wide pH range. The degradation process was dominated by non-radical oxidation pathway after S doping, and the overall process moved towards low toxicity.
ENVIRONMENTAL RESEARCH
(2024)
Article
Environmental Sciences
Srivalli Thimmarayan, Harshavardhan Mohan, Gaddapara Manasa, Karthi Natesan, Shanmugam Mahendran, Pavithra Muthukumar Sathya, Byung-Taek Oh, R. Ravi Kumar, Rangasamy Sigamani Gandhimathi, Arul Jayaprakash, Kamala-Kannan Seralathan
Summary: This study investigated the bacterial degradation of naphthalene (NPT) isolated from crude oil-contaminated soil. Bacillus sp. GN 3.4, a potential bacteria for NPT biodegradation, was isolated and the optimal conditions for NPT degradation were determined. The study suggests that Bacillus sp. GN 3.4 could potentially aid in bioremediation by eliminating NPT from the soil.
ENVIRONMENTAL RESEARCH
(2024)