in this research, recognition of karstic water-bearing zones using the management of exploration data in kal-qorno valley, situated in the tepal area of shahrood, has been considered. for this purpose, the sequential exploration method was conducted using geological evidences and applying remote sensing and geoelectrical resistivity methods in two major phases including the regional and local s...

This work investigates allocation of tasks to multi-robots when tasks are spatially distributed and constrained to be executed within assigned time windows. Our work explores the interaction between scheduling and optimal routing. We propose the Time-Sensitive Sequential Single-Item Auction algorithm as a method to allocate tasks with time windows in multi-robot systems. We show, experimentally...

Future climate forcing data at the temporal and spatial scales needed to drive hydrologic models are not readily available. Simple methods to derive these data from historical data or General Circulation Model (GCM) results may not adequately capture future hydrological variability. This study assessed streamflow response to daily future climate forcing data produced by a new method using subse...

This paper describes a route construction method for the vehicle routing problem with multiple vehicle types and time window constraints. Several insertion-based savings heuristics are presented. The heuristics were tested on twenty-four 100-customer problems modified from the literature. Experimental results demonstrate that heuristics with the consideration of a sequential route construction ...

In recent years, routing has been the most focused area in ad hoc networks research. On-demand routing in particular, is widely developed in bandwidth constrained mobile wireless ad hoc networks because of its effectiveness and efficiency. Most proposed on-demand routing protocols are built and relied on single route for each data session. Whenever there is a link disconnection on the active ro...

Recent studies show that multimodel combinations improve hydroclimatic predictions by reducing model uncertainty. Given that climate forecasts are available from multiple climate models, which could be ingested with multiple watershed models, what is the best strategy to reduce the uncertainty in streamflow forecasts? To address this question, we consider three possible strategies: (1) reduce t...

Recently Gerald Ash has shown through case studies that event dependent routing is attractive in large scale multi-service MPLS networks. In this paper, we consider the application of Load Shared Sequential Routing (LSSR) in MPLS networks where the load sharing factors are updated using reinforcement learning techniques. We present algorithms based on learning automata techniques for optimizing...

Long-term streamflow forecasting is crucial to reservoir scheduling and water resources management. However, due to the complexity of internally physical mechanisms in streamflow process and the influence of many random factors, long-term streamflow forecasting is a difficult issue. In the article, we mainly investigated the ability of the Relevance Vector Machine (RVM) model and its applicabil...

The water balance equation dictates that streamflow may be reduced by transpiration. Yet temporal disequilibrium weakens the relationship between transpiration and streamflow in many cases where inputs and outputs are unbalanced. We address two critical knowledge barriers in ecohydrology with respect to time, scale dependence and lags. Study objectives were to correlate components of the water ...

This thesis summarises development and application of a hydrological model for simulating forest canopy processes, snow accumulation and melt, soil and ground water interactions, and streamflow routing. A motivation behind the model development is to outline a methodology for predicting the influence of land use changes on catchment hydrological processes. In addition, the development aims at p...