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.     

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...     

Independent Base Vector Representation to Address Endmember Variability in Hyperspectral Unmixing

The normal compositional model (NCM) is a well-known and powerful model in hyperspectral unmixing which represents endmembers as independent Gaussian vectors to capture endmember variability. However, the assumption of independent endmembers diminishes the model accuracy because the high degree of correlation between endmembers of a scene and identical sources of variability demonstrate that the endmembers are dependent. This paper proposes a new hyperspectral unmixing algorithm which represents endmembers using dependent Gaussian vectors to estimate abundance fractions. To overcome the higher complexity caused by dependence assumption, this algorithm introduces new independent Gaussian vectors named Base Vectors to represent different endmembers by a weighted linear combination. Also, the proposed unmixing algorithm uses maximum likelihood method to estimate weight coefficients of Base Vectors which are used to represent mixed pixel. Finally, abundance estimation can be done using the new representation for endmembers and mixed pixel. The proposed algorithm is evaluated and compared with other state-of-the-art unmixing algorithms using simulated and real hyperspectral images. Experimental results demonstrate that the proposed unmixing algorithm can unmix pixels composed of correlated endmembers in hyperspectral images in the presence of spectral variability more accurately than previous methods.     

Seismic potential of the North Qazvin zone,Alborz

The North Qazvin region is a part of the Central Alborz Mountains in Iran and has experienced destructive earthquakes. This region is a popular and industrial zone near Tehran, capital of Iran. To identify the highest and lowest seismic hazard location and consequently the seismic zonation of this region, different parameters, such as topography, geology, tectonics and seismicity, have been focused. Accordingly, the north of Qazvin region can be divided into three subzones: western, eastern and southern. Seismic activity of the western zone is higher than the other ones and seismic potential of the eastern zone is higher than the other two zones. This zoning is also necessary for all seismic active areas to find the most dangerous zone.     

Geochemistry of stratabound scheelite mineralisation and associated calc-silicate rocks from Chitral,NE Hindu Kush,Pakistan

Tungsten mineralisation in the NE Hindu Kush terrain occurs 8 km NW of the Tirich Boundary Zone suture between Karakoram and Eastern Hindu Kush. Scheelite occurs mainly in calc-silicate rocks and subordinately in tourmalinites associated with metasediments at Miniki Gol, Chitral. The investigated area underwent two phases of deformation and was metamorphosed up to sillimanite grade, followed by the emplacement of leucogranite and hydrothermal activity. The mineral assemblages of the calc-silicate rocks, comprising clinozoisite, quartz, calcic-amphibole, plagioclase, chlorite, biotite, calcite, sphene, garnet and scheelite, clearly express a skarn type environment. The coexistence of the scheelite grains with clinozoisite and the occurrence of anomalous values of ZrO₂ and Ta₂O₅ in the scheelite grains imply a genetic link between the scheelite mineralisation and post-magmatic hydrothermal fluids. The enrichment of Zr, Hf, Be, Sn, W, Th, U, Ga, Nb, F and Y along with total REE in the scheelite-bearing calc-silicate rocks compared with the associated metasediments assigns that the rocks at Miniki Gol have undergone a pronounced hydrothermal activity. Strong positive correlations between Zr, Hf, Nb, Y, Ta, F and REE, and the mobility of REE are consistent with this consideration. Aqueous fluid inclusions in the scheelite-bearing calc-silicate rocks display very low salinity, suggesting a mixing of magmatic fluids with meteoric water. The formation of intergrown scheelite and clinozoisite indicates a high pH and CO₂-deficient fluid. The tungsten mineralization may be related to the Miniki Gol leucogranite which occurs at a distance of only 400 m.