We review previous approaches to nowcasting earthquakes and introduce new based on deep learning using three distinct models recurrent neural networks transformers. discuss different choices for observables measures presenting promising initial results a region of Southern California from 1950–2020. Earthquake activity is predicted as function 0.1-degree spatial bins time periods varying two we...

Suppes-Sen Dominance is a commonly accepted criterion of impartiality in distributive justice. Mariotti (1999) characterized the Nash bargaining solution using Nash (1950)’s Scale Invariance (SI) axiom and an axiom named Suppes-Sen Proofness (SSP) that embodies the Suppes-Sen principle. By adding a relative equity component to SSP, we …rst consider a stronger version of of it, the Strong Suppes...

In the past two decades, data-driven modeling has become a popular approach for different tasks. This paper presents an evaluation of performance five widely used approaches (i.e., generalized linear model, lasso regression, support vector machine, neural networks, and random forest) Etobicoke Creek watershed in Ontario, Canada. The models are built with eleven years meteorological hydrometric ...

The construction of bridges and other structures across the river will affect flood discharge capacity local water potential river.Based on navier-Stokes equation MIKE21FM hydrodynamic module, this paper carries out two-dimensional numerical simulation part Shixi River. By optimizing grid near piers to reduce difference brought by terrain generalized real river, it simulates analyzes length cur...

Abstract Some hydraulic structures and phenomena, including compound channels, must be studied in relation to open channel flow. Despite the fact that primary watersheds share a similar degree of roughness, estimating discharge composite channels with mainstreams flood plains has proved tricky. The flow for different roughness plain been studied, results computed experimentally using horizontal...

Suspended sediment load (SSL) prediction study is critical to water resource management. This paper presents studies related the of SSL using machine learning (ML) algorithms over last 13 years. research gives a survey current that are used techniques predict on several rivers in different reign. Also, it aims find performance model SSL. done by making comparisons between time scales. Several m...

Many hydrologic and water quality computer models have been developed and applied to assess hydrologic and water quality impacts of land use changes. These models are typically calibrated and validated prior to their application. The Long-Term Hydrologic Impact Assessment (L-THIA) model was applied to the Little Eagle Creek (LEC) watershed and compared with the filtered direct runoff using BFLO...

Hydrologic models are essential to watershed planning and management, particularly in the San Antonio River watershed where competition for scarce water resources is a challenge. As a result, the calibration and validation of hydrologic models are essential steps for their successful application. In this study, we examined the use of a loosely coupled genetic algorithm (GA) as an autocalibratio...

In infinitely repeated games, the act of teaching an outcome to our adversaries can be beneficial to reach coordination, as well as allowing us to ‘steer’ adversaries to outcomes that are more beneficial to us. Teaching works well against followers, agents that are willing to go along with the proposal, but can lead to miscoordination otherwise. In the context of infinitely repeated games there...