Article
Environmental Sciences
Chenghao Zhong, Hao Wang, Qingchun Yang
Summary: Self-organizing maps (SOM) combined with hierarchical clustering were applied to analyze the hydrochemical characteristics of groundwater in the Yinchuan basin. The results identified three principal types of groundwater and revealed the predominant mechanisms in the hydrogeochemical evolution. The study concluded that the combined method of SOM and hierarchical clustering provides a reliable approach for interpreting the hydrochemical characteristics of groundwater with high-dimensional data.
Article
Environmental Sciences
A. T. M. Sakiur Rahman, Yumiko Kono, Takahiro Hosono
Summary: A holistic understanding of hydrochemical features is essential for water resources management and protection. Machine learning techniques like self-organizing map (SOM) can provide more detailed information on hydrochemical processes than traditional approaches, particularly in complex regions. Proper application of SOM is crucial for accurate results.
SCIENCE OF THE TOTAL ENVIRONMENT
(2022)
Article
Geochemistry & Geophysics
Shen Qu, Zheming Shi, Xiangyang Liang, Guangcai Wang, Jiaqian Han
Summary: The study used self-organizing map calculations and traditional multivariate statistical methods to investigate the groundwater chemistry and quality in the Yuheng Coalfield. The findings suggest that water-rock interactions play a significant role in controlling the groundwater chemistry and quality.
JOURNAL OF GEOCHEMICAL EXPLORATION
(2021)
Article
Computer Science, Artificial Intelligence
Akhtar Jamil, Alaa Ali Hameed, Zeynep Orman
Summary: This paper proposes a novel variable learning rate method called VLRSOM to address the challenges of high accuracy with fast convergence and low topological error in the conventional Self-Organizing Maps (SOM). Experimental results show that the proposed method exhibits faster convergence and better topology preservation compared to other SOM techniques. It eliminates the tradeoff between convergence rate and accuracy while maintaining the topological relationship of the data.
COMPLEX & INTELLIGENT SYSTEMS
(2023)
Article
Engineering, Environmental
Emmanouil A. Varouchakis, Dimitri Solomatine, Gerald A. Corzo Perez, Seifeddine Jomaa, George P. Karatzas
Summary: Successful modelling of groundwater level variations in complex aquifer systems requires integration of geostatistics and machine learning approaches. This study focuses on cases with large and randomly distributed datasets in different aquifer types. Self-Organizing Maps are used to identify locally similar data inputs and substitute the uncertain correlation length of the variogram model. Transgaussian Kriging is then applied to estimate the bias-corrected spatial distribution of groundwater level. The proposed methodology shows a significant improvement compared to classical geostatistical approaches.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
(2023)
Article
Engineering, Civil
Li-Chiu Chang, Wu-Han Wang, Fi-John Chang
Summary: The study compared the effectiveness of two SOM training strategies, with the S2 strategy demonstrating higher efficiency and effectiveness in constructing regional flood inundation maps.
JOURNAL OF HYDROLOGY
(2021)
Article
Chemistry, Analytical
Lisiane Esther Ekemeyong Awong, Teresa Zielinska
Summary: The objective of this article is to develop a methodology for selecting the appropriate number of clusters to group and identify human postures using neural networks with unsupervised self-organizing maps. The use of quality scores to determine the number of clusters frees the expert to make subjective decisions about the number of postures, enabling the use of unsupervised learning. The findings show that DS offers good quality in posture recognition, effectively following postural transitions and similarities.
Article
Multidisciplinary Sciences
Rui Wang, Tuo Shi, Xumeng Zhang, Jinsong Wei, Jian Lu, Jiaxue Zhu, Zuheng Wu, Qi Liu, Ming Liu
Summary: This article introduces a hardware implementation of self-organizing maps (SOM) based on memristors, which provides faster computing speed and energy efficiency compared to CMOS digital counterparts. The memristor-based SOM demonstrates improved performance in data clustering, image processing, and optimization problem-solving.
NATURE COMMUNICATIONS
(2022)
Article
Green & Sustainable Science & Technology
Hairu Mao, Guangcai Wang, Zhi Rao, Fu Liao, Zheming Shi, Xujuan Huang, Xianglong Chen, Yang Yang
Summary: This study characterized the spatial variability of groundwater chemistry and associated influencing factors in the Poyang Lake Basin in eastern China. It identified contaminated groundwater with different types and degrees of pollution, analyzed the major factors controlling groundwater chemistry, and highlighted the significance of groundwater management and pollution control in the study area.
JOURNAL OF CLEANER PRODUCTION
(2021)
Article
Environmental Sciences
Shaojie Lv, Zongwen Zhang, Ning Sun, Zheming Shi, Jia Li, Shen Qu
Summary: Groundwater quality assessment is crucial for understanding the suitability of groundwater resources. This study proposed a method combining self-organizing map and entropy-based weight determining method to assess groundwater quality. The study classified sampling points into five clusters, indicating different sources of contamination. The results showed that groundwater affected by domestic sewage discharge sources had better quality compared to other sources in the study area.
FRONTIERS IN ENVIRONMENTAL SCIENCE
(2022)
Article
Geochemistry & Geophysics
Jiayu Chen, Herong Gui
Summary: The shift from traditional small holder farms to semi-intensive and intensive farms in livestock and poultry production systems has resulted in a gradual decline in the quality of shallow groundwater, attracting significant attention from researchers. This study employed self-organizing map technology to identify the impact of livestock and poultry farms on shallow groundwater hydrochemistry. The NO3-N content in water samples from livestock and poultry farms in summer and winter, as well as the NH4-N and NO2-N content in winter, were found to be more susceptible to external influences. Agricultural and industrial activities were identified as important sources of Cl- and SO42- leaching in shallow groundwater. Silicate weathering was found to be a significant source of conventional ions in shallow groundwater in the study area. Water quality in livestock farms was primarily affected by farm activities and agricultural pollution in both summer and winter, while water quality in poultry farms was mainly influenced by industrial sources and natural sources.
Article
Engineering, Civil
Andreas Wunsch, Tanja Liesch, Stefan Broda
Summary: Hydrograph clustering is important for identifying dynamic patterns within aquifers systems and effectively managing groundwater resources. A developed unsupervised modeling approach, incorporating feature-based clustering and a combination of Self-Organizing Maps with a modified DS2L-Algorithm, successfully characterized and clustered hydrographs on a regional scale. The framework showed adaptive capability to identify homogeneous groups of hydrograph dynamics, with spatially known and unknown patterns that correspond to external controlling factors in the test area.
WATER RESOURCES MANAGEMENT
(2022)
Article
Computer Science, Hardware & Architecture
Xiaofei Qu, Lin Yang, Kai Guo, Linru Ma, Meng Sun, Mingxing Ke, Mu Li
Summary: This paper provides a focused literature survey on self-organizing maps (SOM) for intrusion detection, categorizing them into static-layered and dynamic-layered architectures. HSOM reduces computational overheads and efficiently represents data hierarchy, while GHSOM is effective for online intrusion detection with low computing latency, dynamic adaptability, and self-learning capabilities.
MOBILE NETWORKS & APPLICATIONS
(2021)
Article
Geosciences, Multidisciplinary
Alanny Christiny Costa Melo, David Lopes de Castro, Stephen James Fraser, Antomat Avelino Macedo Filho
Summary: This research utilized multivariate analysis and the Self-Organizing Maps (SOM) method to analyze the magnetic and gamma-spectrometric signatures of dyke swarms in Northeast Brazil, revealing their spatial distribution and characteristics. The SOM analysis identified populations associated with the dyke swarms, reducing the ambiguity of magnetic anomaly interpretation, and these results were validated through fieldwork.
JOURNAL OF APPLIED GEOPHYSICS
(2021)
Article
Engineering, Electrical & Electronic
Fei Du, Yu Zhang, Xiongwen Zhao, Suiyan Geng, Zihao Fu, Xiaoqing Wang, Lujia Yu, Qingliang Li
Summary: In this article, a self-organizing map with time-varying topological structure (SOM-TVS) clustering algorithm is proposed for optimizing wireless channel models. The algorithm does not require any prior knowledge and has a low complexity.
IEEE TRANSACTIONS ON ANTENNAS AND PROPAGATION
(2023)
Article
Engineering, Civil
Arfan Arshad, Ali Mirchi, Javier Vilcaez, Muhammad Umar Akbar, Kaveh Madani
Summary: High-resolution, continuous groundwater data is crucial for adaptive aquifer management. This study presents a predictive modeling framework that incorporates covariates and existing observations to estimate groundwater level changes. The framework outperforms other methods and provides reliable estimates for unmonitored sites. The study also examines groundwater level changes in different regions and highlights the importance of effective aquifer management.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Lihua Chen, Jie Deng, Wenzhe Yang, Hang Chen
Summary: A new grid-based distributed karst hydrological model (GDKHM) is developed to simulate streamflow in the flood-prone karst area of Southwest China. The results show that the GDKHM performs well in predicting floods and capturing the spatial variability of karst system.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Faruk Gurbuz, Avinash Mudireddy, Ricardo Mantilla, Shaoping Xiao
Summary: Machine learning algorithms have shown better performance in streamflow prediction compared to traditional hydrological models. In this study, researchers proposed a methodology to test and benchmark ML algorithms using artificial data generated by physically-based hydrological models. They found that deep learning algorithms can correctly identify the relationship between streamflow and rainfall in certain conditions, but fail to outperform traditional prediction methods in other scenarios.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Yadong Ji, Jianyu Fu, Bingjun Liu, Zeqin Huang, Xuejin Tan
Summary: This study distinguishes the uncertainty in drought projection into scenario uncertainty, model uncertainty, and internal variability uncertainty. The results show that the estimation of total uncertainty reaches a minimum in the mid-21st century and that model uncertainty is dominant in tropical regions.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Z. R. van Leeuwen, M. J. Klaar, M. W. Smith, L. E. Brown
Summary: This study quantifies the effectiveness of leaky dams in reducing flood peak magnitude using a transfer function noise modelling approach. The results show that leaky dams have a significant but highly variable impact on flood peak magnitude, and managing expectations should consider event size and type.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Zeda Yin, Yasaman Saadati, M. Hadi Amini, Linlong Bian, Beichao Hu
Summary: Combined sewer overflows pose significant threats to public health and the environment, and various strategies have been proposed to mitigate their adverse effects. Smart control strategies have gained traction due to their cost-effectiveness but face challenges in balancing precision and computational efficiency. To address this, we propose exploring machine learning models and the inversion of neural networks for more efficient CSO prediction and optimization.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Qimou Zhang, Jiacong Huang, Jing Zhang, Rui Qian, Zhen Cui, Junfeng Gao
Summary: This study developed a N-cycling model for lowland rural rivers covered by macrophytes and investigated the N imports, exports, and response to sediment dredging. The findings showed a considerable N retention ability in the study river, with significant N imports from connected rivers and surrounding polders. Sediment dredging increased particulate nitrogen resuspension and settling rates, while decreasing ammonia nitrogen release, denitrification, and macrophyte uptake rates.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Xue Li, Yingyin Zhou, Jian Sha, Man Zhang, Zhong-Liang Wang
Summary: High-resolution climate data is crucial for predicting regional climate and water environment changes. In this study, a two-step downscaling method was developed to enhance the spatial resolution of GCM data and improve the accuracy for small basins. The method combined medium-resolution climate data with high-resolution topographic data to capture spatial and temporal details. The downscaled climate data were then used to simulate the impacts of climate change on hydrology and water quality in a small basin. The results demonstrated the effectiveness of the downscaling method for spatially differentiated simulations.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Tongqing Shen, Peng Jiang, Jiahui Zhao, Xuegao Chen, Hui Lin, Bin Yang, Changhai Tan, Ying Zhang, Xinting Fu, Zhongbo Yu
Summary: This study evaluates the long-term interannual dynamics of permafrost distribution and active layer thickness on the Tibetan Plateau, and predicts future degradation trends. The results show that permafrost area has been decreasing and active layer thickness has been increasing, with an accelerated degradation observed in recent decades. This has significant implications for local water cycle processes, water ecology, and water security.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Chi Zhang, Xu Zhang, Qiuhong Tang, Deliang Chen, Jinchuan Huang, Shaohong Wu, Yubo Liu
Summary: Precipitation over the Tibetan Plateau is influenced by systems such as the Asian monsoons, the westerlies, and local circulations. The Indian monsoon, the westerlies, and local circulations are the main systems affecting precipitation over the entire Tibetan Plateau. The East Asian summer monsoon primarily affects the eastern Tibetan Plateau. The Indian monsoon has the greatest influence on precipitation in the southern and central grid cells, while the westerlies have the greatest influence on precipitation in the northern and western grid cells. Local circulations have the strongest influence on the central and eastern grid cells.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Manuel Almeida, Antonio Rodrigues, Pedro Coelho
Summary: This study aimed to improve the accuracy of Total Phosphorus export coefficient models, which are essential for water management. Four different models were applied to 27 agroforestry watersheds in the Mediterranean region. The modeling approach showed significant improvements in predicting the Total Phosphorus diffuse loads.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Yutao Wang, Haojie Yin, Ziyi Wang, Yi Li, Pingping Wang, Longfei Wang
Summary: This study investigated the distribution and transformation of dissolved organic nitrogen (DON) in riverbed sediments impacted by effluent discharge. The authors found that the spectral characteristics of dissolved organic matter (DOM) in surface water and sediment porewater could be used to predict DON variations in riverbed sediments. Random forest and extreme gradient boosting machine learning methods were employed to provide accurate predictions of DON content and properties at different depths. These findings have important implications for wastewater discharge management and river health.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Saba Mirza Alipour, Kolbjorn Engeland, Joao Leal
Summary: This study assesses the uncertainty associated with 100-year flood maps under different scenarios using Monte Carlo simulations. The findings highlight the importance of employing probabilistic approaches for accurate and secure flood maps, with the selection of probability distribution being the primary source of uncertainty in precipitation.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Janine A. de Wit, Marjolein H. J. van Huijgevoort, Jos C. van Dam, Ge A. P. H. van den Eertwegh, Dion van Deijl, Coen J. Ritsema, Ruud P. Bartholomeus
Summary: The study focuses on the hydrological consequences of controlled drainage with subirrigation (CD-SI) on groundwater level, soil moisture content, and soil water potential. The simulations show that CD-SI can improve hydrological conditions for crop growth, but the success depends on subtle differences in geohydrologic characteristics.
JOURNAL OF HYDROLOGY
(2024)
Article
Engineering, Civil
Constantin Seidl, Sarah Ann Wheeler, Declan Page
Summary: Water availability and quality issues will become increasingly important in the future due to climate change impacts. Managed Aquifer Recharge (MAR) is an effective water management tool, but often overlooked. This study analyzes global MAR applications and identifies the key factors for success, providing valuable insights for future design and application.
JOURNAL OF HYDROLOGY
(2024)