Sensitivity analysis of monthly reference crop evapotranspiration trends in Iran: a qualitative approach

Theoretical and Applied Climatology - The main objective of this study was to analyze the sensitivity of the monthly reference crop evapotranspiration (ETo) trends to key climatic factors (minimum...     

An intelligent spatial land use planning support system using socially rational agents

This research presents an intelligent planning support system based on multi-agent systems for spatial urban land use planning. The proposed system consists of two main phases: a pre-negotiation phase and an automated negotiation phase. The pre-negotiation phase involves interaction between human actors and intelligent software agents in order to elicit the actors’ social preferences. The agents employ social value orientation theory, which is rooted in social psychology, in order to model actors’ social preferences. The automated negotiation phase involves negotiation among autonomous software agents, the aim being to achieve consensus about the spatial problem on behalf of the relevant actors and using the information obtained.

This study employs a computationally effective Bayesian learning technique, along with social value orientation theory, to design socially rational intelligent agents who work on behalf of real actors. The proposed system is applied to a real world urban land use planning case study. Human actors participate in a pre-negotiation phase, and their social preferences are elicited by intelligent software agents through a number of interactions. Then, software agents come together to engage in an automated negotiation phase and eventually reach an agreement on the spatial configuration of urban land uses on behalf of the actors. The results of the study show that the proposed system is effective at performing an automated negotiation, plus that the final plan – which is the output of the automated negotiation – produces higher social utility and better spatial land use configurations for the agents.     

Application of artificial intelligence techniques in automatic hull form generation

The paper describes a methodology for automatic hull form generation of ships with some desired performances using artificial intelligence techniques. The whole implementation process is divided into three main components. First of all the half-breadth weight matrices are generated that would provide population with pre-fitness by examining the relationship of the hull form with the principal dimensions of a number of existing vessels. Secondly, breadth and draft are adjusted using Neural Network Concepts. Breadth, draft, length, displacement and speed of the ship are very related terms and relations among them create some constraints. Neural Networks solve these constraints and adjust the parameters. Finally, Genetic Algorithm is used for searching the exact solution by examining several generations. For this, the algorithms need to measure fitness for every population in every generation. Unfortunately, GA doesn't guarantee fairness of the surface of the hull form, which can't be ignored. So, for every population especially for newborn population fairing techniques would be used. However, being complex geometric shape, hull form surface can't be faired using least-square or other single equation fitting techniques. Fairness is done taking pair-wise points using B-spline functions [CAD 20(1988)].     

Spatiotemporal reference evapotranspiration changes in humid and semi-arid regions of Iran: past trends and future projections

Theoretical and Applied Climatology - This study was undertaken to investigate the reference evapotranspiration (ET0) changes in semi-arid and humid regions of Iran during the past...     

Assessment of in situ permeability with emphasis on packer testing in Kuwait

This paper discusses in situ permeability testing performed at two sites in bore holes drilled in an extensive hydrogeological exploration program in Kuwait. The testing program, comprising packer, falling and rising head tests, was carried out in calcareous and variedly textured cemented sand formed during post-depositional diagenetic processes with the colloquial name ‘Gatch’. The program was undertaken to assist in the design and construction of a pilot drainage scheme aimed at lowering of the groundwater table in Kuwait City and suburbs.

The results indicated that ‘Gatch’ is an almost impermeable soil. However, the hydraulic conductivity of the subsoils at the investigated sites is significantly influenced by the distribution and volume of macropores. These permeable zones act as preferential pathways for the movement of water bypassing the fine matrix and, thereby, improve markedly the overall drainage characteristics of the sites.

Various in situ test methods, including packer, compare results satisfactorily, to give the sites a variable hydraulic conductivity rating that straddles between very low and medium. The packer device, by faring well against other routine in situ tests, shows promises for use as a tool in the assessment of drainage parameters of cemented soils. Laboratory tests, performed in parallel, proved inadequate to characterize the permeability properties of the subsoils in Kuwait.