Article
Computer Science, Interdisciplinary Applications
Baohua Yang, Jinshuai Zhao, Haidan Zhao
Summary: The ability to obtain robust ranking results is crucial when choosing a method for multiple criteria decision-making (MCDM). However, the rank reversal phenomenon in MCDM, particularly in the technique for order preference by similarity to ideal solution (TOPSIS), compromises its credibility. Although some research papers have proposed solutions to minimize or avoid rank reversal in TOPSIS, there are still gaps that require further investigation. These gaps include the inability to completely eliminate rank reversal, the need for more decision information, and the lack of theoretical guarantees for ranking stability. To address these issues, an improved TOPSIS method, named IE-TOPSIS, is developed based on information expansion and virtual ideal points. The IE-TOPSIS method effectively avoids the influence of data standardization on ranking by constructing an algorithm for the extreme value extension of criteria indicators. Additionally, the concept of a virtual ideal point is proposed to prevent rank reversal caused by changes in ideal points. The paper proves that the IE-TOPSIS method satisfies the given definition of ranking robustness, theoretically guaranteeing the absence of rank reversal. The paper also proposes a new ranking index that better distinguishes evaluation objects and solves the limitations of the classic TOPSIS ranking index. The results of example verification demonstrate that the improved TOPSIS method aligns strongly with theoretical analysis and effectively handles rank reversal in comparison to other studies.
COMPUTERS & INDUSTRIAL ENGINEERING
(2022)
Article
Engineering, Marine
Xiaodan Yang, Shan Zhou, Shengchang Zhou, Zhenya Song, Weiguo Liu
Summary: High-resolution global ocean general circulation models are crucial for accurate ocean forecasting, but operational forecasting systems face challenges due to high computational demand and low parallel efficiency. A new communication-avoiding Krylov subspace method (CA-PCG) was developed to improve scalability by reducing communication costs, resulting in significant reductions in execution time and an increase in speedup ratio. The effectiveness of CA-PCG in improving process count scalability demonstrates its potential as an efficient solution for precise ocean simulation.
JOURNAL OF MARINE SCIENCE AND ENGINEERING
(2021)
Article
Engineering, Environmental
Mahrukh Yousaf, Zulfiqar Ali, Muhammad Mohsin, Maryam Ilyas, Muhammad Shakeel
Summary: This study proposes a new weighting scheme called weighted aggregation (WA) and introduces the Multi-model weighted drought severity index (MMWDSI) as an improved indicator for drought assessment. The MMWDSI approach involves ensemble modeling using the WA scheme and incorporating the K-components Gaussian mixture model (K-CGMM) for appropriate distribution fitting. It proves to be a flexible and effective method that enhances accuracy in drought monitoring, allowing for inferring extreme events and assessing trends.
STOCHASTIC ENVIRONMENTAL RESEARCH AND RISK ASSESSMENT
(2023)
Article
Environmental Sciences
Saikat Sengupta, Sourendra Kumar Bhattacharya, Nimya Sheena Sunil, Sumit Sonar
Summary: Raindrop evaporation is an important sub-cloud process that affects rainfall amount and rainwater isotope values. Inaccurate estimation of this process during Indian summer monsoon can lead to significant biases in model simulations. This study investigates the relationship between raindrop evaporation and isotope biases, and finds that lower estimates of evaporation may be responsible for the biases in two GCMs.
Article
Meteorology & Atmospheric Sciences
Veeshan Narinesingh, James F. Booth, Yi Ming
Summary: This study examines the climatology and dynamics of atmospheric blocking in GFDL's atmosphere-only (AM4) and coupled atmosphere-ocean (CM4) comprehensive models. The models capture the correct blocking climatology and planetary-scale signatures of the stationary wave, but some regional biases exist. The models generate excessive blocking frequency and too strong of a stationary wave in the eastern Pacific and over western North America, while in the Atlantic, they produce too little blocking and a weakened stationary wave.
JOURNAL OF CLIMATE
(2022)
Article
Environmental Sciences
Sharad Kumar Gupta, Dericks P. Shukla
Summary: Most of the research studies on landslide susceptibility mapping in the Himalayan region focus on small subsets of geomorphological features and the selected study area may not accurately represent landslide occurrences in the whole basin. This study analyzes the effect of scale in landslide susceptibility mapping and compares two widely known techniques. The results show that logistic regression performs better for larger scales, while discriminant analysis performs better for smaller scales.
ENVIRONMENTAL EARTH SCIENCES
(2022)
Article
Environmental Sciences
Debra Simecek-Beatty, William J. Lehr
Summary: In the event of an oil spill, emergency responders must quickly deploy cleanup and protection equipment based on forecast trajectory guidance. However, there is a need to improve the current performance metrics used for assessing the quality of spill forecasts, which lack appropriate numerical model accuracy scores and spatial resolution limits for useful forecast information.
MARINE POLLUTION BULLETIN
(2021)
Article
Meteorology & Atmospheric Sciences
B. Deepthi, Bellie Sivakumar
Summary: This study evaluates the performance of 49 General Circulation Models (GCMs) in simulating rainfall in India using complex networks. The results show that different GCMs perform well in simulating whole-year rainfall and summer monsoon rainfall. The clustering coefficient-based analysis helps narrow down the ensemble of best-performing GCMs.
ATMOSPHERIC RESEARCH
(2022)
Article
Green & Sustainable Science & Technology
Renan Felinto de Farias Aires, Luciano Ferreira
Summary: This study presents a new material selection approach based on the TOPSIS method, which solves the rank reversal problem in multi-criteria decision-making methods and applies to sustainable material selection.
Article
Materials Science, Textiles
Subhasis Das, Anindya Ghosh
Summary: A new method for grading raw jute is proposed in this study, using fuzzy multi-criteria decision-making and intuitionistic multi-expert decision-making to reduce the fuzziness in jute quality parameters. The results show that this intuitionistic approach is significant for grading highly heterogenic bio-materials like jute.
JOURNAL OF NATURAL FIBERS
(2021)
Article
Economics
Bhanu Pratap Singh, Akash Yadav, Kailash Chandra Pradhan
Summary: Due to the limited capacity of formal learning institutions, informal learning is the main source of skill acquisition for a majority of the population in India. However, many skilled workers in India face lower wages and difficulty finding employment due to a lack of skill certification. This study examines the impact of skill certification on monthly wages, finding that certified workers earn higher wages due to factors such as extended training, superior occupational status, higher education level, and job experience. Reducing the wage gap caused by skill certification is crucial for improving competitiveness, efficiency, and productivity in the Indian labor market.
JOURNAL OF THE KNOWLEDGE ECONOMY
(2023)
Article
Meteorology & Atmospheric Sciences
Jiaying Zhang, Kaiyu Guan, Rong Fu, Bin Peng, Siyu Zhao, Yizhou Zhuang
Summary: This study evaluates the seasonal forecasts of three climate variables in South America and attributes the source of prediction errors. The European Centre for Medium-Range Weather Forecasts (ECMWF) model has the highest quality among the evaluated models. Forecasts of vapor pressure deficit and temperature have better agreement with observations compared to precipitation. The degradation of forecasts with increasing lead times is due to the failure of capturing local circulation patterns and the overestimation of ENSO's influence.
JOURNAL OF HYDROMETEOROLOGY
(2023)
Article
Mathematics, Applied
Ruixia Yuan, Bo Jiang, Yongge Tian
Summary: In practical applications, if a true regression model is misspecified in some forms, the estimation and inference results obtained under the true and misspecified models may differ. Therefore, it is important to compare these results and establish links between them to explain and utilize the misspecified models effectively.
Article
Meteorology & Atmospheric Sciences
Rucun Han, Zhanling Li, Yuanyuan Han, Pengying Huo, Zhanjie Li
Summary: General circulation models (GCMs) are used to simulate past and future climate, and their roles in water resources planning/management are recognized globally. However, the variability and uncertainty in future climate projections of GCMs have led to criticism from water resources planners. This paper compares the advantages and disadvantages of selecting the optimal single GCM versus a multi-model ensemble (MME) using the TOPSIS method.
INTERNATIONAL JOURNAL OF CLIMATOLOGY
(2023)
Article
Statistics & Probability
Jack Jewson, David Rossell
Summary: Statisticians often face the choice of using probability models or minimizing loss functions. This paper proposes a method that combines the Hyvarinen score and general Bayesian updating to handle losses that lead to improper models. Through the Script capital H-score, the paper proves that this method consistently selects the model closest to the data-generating truth in Fisher's divergence. It also demonstrates the ability to learn optimal hyper-parameters for loss functions.
JOURNAL OF THE ROYAL STATISTICAL SOCIETY SERIES B-STATISTICAL METHODOLOGY
(2022)
Article
Meteorology & Atmospheric Sciences
K. Srinivasa Raju, P. Sonali, D. Nagesh Kumar
THEORETICAL AND APPLIED CLIMATOLOGY
(2017)
Article
Environmental Sciences
Sonali Pattanayak, Ravi S. Nanjundiah, D. Nagesh Kumar
ENVIRONMENTAL RESEARCH LETTERS
(2017)
Article
Remote Sensing
Hassan Rangaswamy Shwetha, Dasika Nagesh Kumar
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2018)
Article
Geography, Physical
Subir Paul, D. Nagesh Kumar
ISPRS JOURNAL OF PHOTOGRAMMETRY AND REMOTE SENSING
(2018)
Article
Water Resources
H. R. Shwetha, D. Nagesh Kumar
HYDROLOGICAL SCIENCES JOURNAL-JOURNAL DES SCIENCES HYDROLOGIQUES
(2018)
Article
Engineering, Civil
Chandan Banerjee, D. Nagesh Kumar
WATER RESOURCES MANAGEMENT
(2018)
Article
Chemistry, Analytical
Lanka Karthikeyan, Ming Pan, Dasika Nagesh Kumar, Eric F. Wood
Article
Engineering, Civil
Subir Paul, Chandan Banerjee, D. Nagesh Kumar
JOURNAL OF HYDROLOGIC ENGINEERING
(2020)
Article
Geochemistry & Geophysics
Subir Paul, D. Nagesh Kumar
Summary: Hyperspectral data are more resourceful than multispectral data, but the absence of a space-borne sensor and high cost of airborne sensors restrict the use of HS data. The proposed CNNR model for MS to quasi-HS data transformation is more efficient than existing models and proven to be valuable for crop classification applications.
IEEE TRANSACTIONS ON GEOSCIENCE AND REMOTE SENSING
(2021)
Article
Remote Sensing
Subir Paul, Mamta Kumari, C. S. Murthy, D. Nagesh Kumar
Summary: This study utilizes Synthetic Aperture Radar (SAR) data and deep learning technique to conduct pre-harvest crop mapping in a large geographic area of central India. The results show that combining VH and VV data performs better, with an overall accuracy of 91.75%. The crop map can be generated as early as 45 days prior to harvesting with an accuracy of 89.15%. The 2D-CNN algorithm outperforms SVM and RF techniques, and the methodology can be applied to similar regions.
INTERNATIONAL JOURNAL OF REMOTE SENSING
(2022)
Review
Engineering, Civil
Ashok Mishra, Sourav Mukherjee, Bruno Merz, Vijay P. Singh, Daniel B. Wright, Gabriele Villarini, Subir Paul, D. Nagesh Kumar, C. Prakash Khedun, Dev Niyogi, Guy Schumann, Jery R. Stedinger
Summary: This review provides a comprehensive overview of current flood research, challenges, and future directions, emphasizing the increased flood risk in future urban systems due to continued climate change and land-use intensification. More work is needed for accurate urban flood prediction, quantifying the socioeconomic impacts of floods, and developing mitigation strategies. Integration of multiscale models, stakeholder input, and social and citizen science input is crucial to bridge the gap between model capabilities and end-user needs for flood monitoring, mapping, and dissemination. Additionally, effort is needed for downscaled, ensemble scenarios, data assimilation approaches, and enhanced capabilities for modeling compound hazards and reducing social vulnerability and impacts. Transdisciplinary research between science, policymakers, and stakeholders is essential to reduce flood risk and social vulnerability in the face of dynamic and complex interactions between climate, societal change, watershed processes, and human factors.
JOURNAL OF HYDROLOGIC ENGINEERING
(2022)
Article
Environmental Sciences
Elizabeth Baby George, Cecile Gomez, D. Nagesh Kumar, Subramanian Dharumarajan, Manickam Lalitha
Summary: Hyperspectral imaging spectroscopy is a useful tool for mapping soil properties at large scales. This study analyzed the impact of bare soil pixel identification on clay content estimation using two methods: spectral indices and spectral unmixing. The results showed that the spectral unmixing method provided slightly better performances in estimating clay content, although it reduced the spatial coverage.
GEOCARTO INTERNATIONAL
(2022)
Article
Water Resources
Rajesh Kumar Sah, D. Nagesh Kumar, Apurba Kumar Das
Summary: This study presents a novel account of avulsion records in the Himalayan foreland region from 1990 to 2019, revealing that the eastern Brahmaputra plains are among the most affected areas. The study also suggests that smaller tributaries with transitional reaches are more susceptible to avulsions.
HYDROLOGICAL SCIENCES JOURNAL
(2022)
Article
Engineering, Electrical & Electronic
Subir Paul, Vinayaraj Poliyapram, Nevrez Imamoglu, Kuniaki Uto, Ryosuke Nakamura, D. Nagesh Kumar
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2020)
Article
Engineering, Electrical & Electronic
Hassan Rangaswamy Shwetha, Dasika Nagesh Kumar
IEEE JOURNAL OF SELECTED TOPICS IN APPLIED EARTH OBSERVATIONS AND REMOTE SENSING
(2020)
