An Agent‐Based Simulation of Residential Location Choice of Tenants in Tehran,Iran

Residential location choice modeling is one of the substantial components of land use and transportation models. While numerous aggregated mathematical and statistical approaches have been developed to model the residence choice behavior of households, disaggregated approaches such as the agent‐based modeling have shown interesting capabilities. In this article, a novel agent‐based approach is developed to simulate the residential location choice of tenants in Tehran, the capital of Iran. Tenants are considered as agents who select their desired residential alternatives according to their characteristics and preferences for various criteria such as the rent, accessibility to different services and facilities, environmental pollution, and distance from their workplace and former residence. The choice set of agents is limited to their desired residential alternatives by applying a constrained NSGA‐II algorithm. Then, agents compete with each other to select their final residence among their alternatives. Results of the proposed approach are validated by comparing simulated and actual residences of a sample of tenants. Results show that the proposed approach is able to accurately simulate the residence of 59.3% of tenants at the traffic analysis zone level.     

塔克拉玛干沙漠沙垄起伏地形夏季地表温度差异特征

摘 要：开展塔克拉玛干沙漠沙垄起伏地形夏季地表温度观测试验,旨在为塔克拉玛干沙漠环境陆面过程研究提供科学依据。2019年6月7日至9月2日在塔中地区,沿沙垄迎风坡以及背风坡底部、中部、上部、顶点及垄间谷地共设8个地表温度观测点。结果表明：（1）夏季沙垄地表温度最高温出现在垄间谷地,为74.63 ℃,最低温出现在迎风坡底部,为10.52 ℃;地表温度一天中在7:00左右达到最低,15:00左右达到最高。（2）晴天、多云以及浮尘天各观测点地表温度日均变化曲线呈单峰型,降水、扬沙及沙尘暴天呈双峰型;地表温度的最高温与日均值最大值均出现在晴天的垄间谷地,地表温度的最低温及日均值最小值均出现在降水天的迎风坡底部。（3）沙垄顶点与两个底部最大温差范围是顶点与背风坡底部在晴天的温差范围,为0～18.62 ℃,最小温差范围是顶点与迎风坡底部在降水天的温差范围,为0.01～6.18 ℃;迎风坡和背风坡在晴天地表温度温差范围最大,为0.01～16.93 ℃,在降水天温差范围最小,为0.01～4.15 ℃;顶点与两个底部夏季综合温差范围在0～18.62 ℃,迎风坡与背风坡夏季综合温差范围为0～16.93 ℃。塔克拉玛干沙漠地表温度受典型天气影响变化类型多样,沙垄顶点与底部、迎风坡与背风坡地表温度差异受风力及地形作用明显。     

A new integration scheme for application to seismic hybrid simulation

Hybrid simulation is a powerful test method for evaluating the seismic performance of structural systems. This method makes it feasible that only critical components of a structure be experimentally tested. This paper presents a newly proposed integration algorithm for seismic hybrid simulation which is aimed to extend its capabilities to a wide range of systems where existing methods encounter some limitations. In the proposed method, which is termed the variable time step (VTS) integration method, an implicit scheme is employed for hybrid simulation by eliminating the iterative phase on experimental element, the phase which is necessary in regular implicit applications. In order to study the effectiveness of the VTS method, a series of numerical investigations are conducted which show the successfulness of the VTS method in obtaining accurate, stable and converged responses. Then, in a comparative approach, the improved accuracy of the VTS method over commonly used integration methods is demonstrated. The stability of the VTS method is also studied and the results show that it provides conditional stability; however, its stability limit is well beyond the accuracy limit. The effect of time delay on the VTS method results is also investigated and it is shown that the VTS method is quite successful in handling this experimental error.     

Lithology-dependent seismic anisotropic amplitude variation with offset correction in transversely isotropic media

Analysis of amplitude variation with offset is an essential step for reservoir characterization. For an accurate reservoir characterization, the amplitude obtained with an isotropic assumption of the reservoir must be corrected for the anisotropic effects. The objective is seismic anisotropic amplitude correction in an effective medium, and, to this end, values and signs of anisotropic parameter differences (Δδ and Δε) across the reflection interfaces are needed. These parameters can be identified by seismic and well log data. A new technique for anisotropic amplitude correction was developed to modify amplitude changes in seismic data in transversely isotropic media with a vertical axis of symmetry. The results show that characteristics of pre-stack seismic data, that is, amplitude variation with offset gradient, can be potentially related to the sign of anisotropic parameter differences (Δδ and Δε) between two layers of the reflection boundary. The proposed methodology is designed to attain a proper fit between modelled and observed amplitude variation with offset responses, after anisotropic correction, for all possible lithofacies at the reservoir boundary. We first estimate anisotropic parameters, that is, δ and ε, away from the wells through Backus averaging of elastic properties resulted from the first pass of isotropic pre-stack seismic inversion, on input data with no amplitude correction. Next, we estimate the anisotropic parameter differences at reflection interfaces (values and signs of Δδ and Δε). We then generate seismic angle gather data after anisotropic amplitude correction using Rüger's equation for the P-P reflection coefficient. The second pass of isotropic pre-stack seismic inversion is then performed on the amplitude-corrected data, and elastic properties are estimated. Final outcome demonstrates how introduced methodology helps to reduce the uncertainty of elastic property prediction. Pre-stack seismic inversion on amplitude-corrected seismic data results in more accurate elastic property prediction than what can be obtained from non-corrected data. Moreover, a new anisotropy attribute (ν) is presented for improvement of lithology identification.     

The bituminous mixtures of Tall-e Abu Chizan: A Vth millennium BC settlement in southwestern Iran

Various bituminous artifacts were excavated from the Tall-e Abu Chizan, a late prehistoric (Middle Susiana to Middle Uruk) settlement on the middle of the Curvy plain, between the Karun River and the Ram Hormoz Plain. All samples dated from the Vth millennium BC and cover three periods: 5000–4700 BC (Late Middle Susiana), 4700–4200 BC (Late Susiana 1) and 4200–3900 BC (Late Susiana 2). The bitumens were studied using the techniques of petroleum geochemistry and were compared both to the unaltered crude oils produced from the main oil fields in the area and to the famous Mamatain oil seeps. All samples are very rich in bitumen (average 46 wt%) which has been biodegraded and oxidized. Despite these alteration phenomena, δ¹³C of asphaltenes occur within a narrow range of less than 1‰ PDB. Biodegradation affected the steranes, terpanes, dibenzothiophenes and mono- and triaromatic steroids. Molecular characteristics of terpanes, especially the occurrence of 18α (H)-oleanane, suggest that the bitumen from Tall-e Abu Chizan is a mixture generated from Cretaceous Kazdhumi and Eocene Pabdeh petroleum source rocks. In that respect, bitumens from Tall-e Abu Chizan belong to the same oil family as oil from the Naft Safid field, which is in the vicinity of the archaeological site. In fact, the bitumen at Tall-e Abu Chizan likely originated from oil seepages at Naft Safid. These oil seeps have not yet been sampled or analysed.     

Extraction of forward-directivity velocity pulses using S-Transform-based signal decomposition technique

Robust methods for time-frequency analysis of time series, which provide local information of signals, allow earthquake engineers to study both the input and output of dynamic time history analysis with more reliability. Moreover, time-frequency representations (TFRs) have a major role in the analysis of non-stationary seismic signals exhibiting significant time variation of frequency content. S-Transform (ST) is a modern TFR, which can measure local characteristics of a signal such as amplitude, frequency, and phase at any time instant. This paper presents a new method for decomposition of ground motion signals. A modified version of ST-based technique, originally employed to decompose signals of gearbox vibration, is introduced and applied to the extraction and characterization of pulse-like part of near-fault velocity records, which is contributed to the directivity effects. In addition, a new definition based on ST analysis is used to identify pulse period. The results of implementation of proposed procedure on a database of pulse-like ground motion recordings belonging to the different ranges of magnitude demonstrate the efficiency of proposed method compared with other available approaches. The results, also, indicate that simple approximation of distinct pulses using single-period waveforms, unlike the extracted pulses, cannot represent the impulsive nature of real records adequately.     

Application of wavelet-artificial intelligence hybrid models for water quality prediction: a case study in Aji-Chay River,Iran

The accuracy of Artificial Neural Network (ANN), Adaptive Neuro-Fuzzy Inference System (ANFIS), wavelet-ANN and wavelet-ANFIS in predicting monthly water salinity levels of northwest Iran’s Aji-Chay River was assessed. The models were calibrated, validated and tested using different subsets of monthly records (October 1983 to September 2011) of individual solute (Ca²⁺, Mg²⁺, Na⁺, SO₄ ^2? and Cl^?) concentrations (input parameters, meq L^?1), and electrical conductivity-based salinity levels (output parameter, µS cm^?1), collected by the East Azarbaijan regional water authority. Based on the statistical criteria of coefficient of determination (R²), normalized root mean square error (NRMSE), Nash–Sutcliffe efficiency coefficient (NSC) and threshold statistics (TS) the ANFIS model was found to outperform the ANN model. To develop coupled wavelet-AI models, the original observed data series was decomposed into sub-time series using Daubechies, Symlet or Haar mother wavelets of different lengths (order), each implemented at three levels. To predict salinity input parameter series were used as input variables in different wavelet order/level-AI model combinations. Hybrid wavelet-ANFIS (R² = 0.9967, NRMSE = 2.9 × 10^?5 and NSC = 0.9951) and wavelet-ANN (R² = 0.996, NRMSE = 3.77 × 10^?5 and NSC = 0.9946) models implementing the db4 mother wavelet decomposition outperformed the ANFIS (R² = 0.9954, NRMSE = 3.77 × 10^?5 and NSC = 0.9914) and ANN (R² = 0.9936, NRMSE = 3.99 × 10^?5 and NSC = 0.9903) models.     

Neutral-neutral reactions for the formation of C3O and C3S

We investigate, neutral-neutral radiative association reactions (C₂+CO) and (C₂+CS) for the formation of C₃O and C₃S respectively by DFT. Both the reactions are spin allowed and found to be exothermic and barrierless in nature. The product of these reactions are perfectly linear and the calculated rotational transitions are in good agreement with earlier published data. At the DFT/TZ2P level, the difference between the calculated rotational constant and experimental one is 0.064 % for C₃O and 0.16 % for C₃S. We also discussed the intrinsic and relative stability of these molecules.     

Automatic urban building boundary extraction from high resolution aerial images using an innovative model of active contours

To present a new method for building boundary detection and extraction based on the active contour model, is the main objective of this research. Classical models of this type are associated with several shortcomings; they require extensive initialization, they are sensitive to noise, and adjustment issues often become problematic with complex images. In this research a new model of active contours has been proposed that is optimized for the automatic building extraction. This new active contour model, in comparison to the classical ones, can detect and extract the building boundaries more accurately, and is capable of avoiding detection of the boundaries of features in the neighborhood of buildings such as streets and trees. Finally, the detected building boundaries are generalized to obtain a regular shape for building boundaries. Tests with our proposed model demonstrate excellent accuracy in terms of building boundary extraction. However, due to the radiometric similarity between building roofs and the image background, our system fails to recognize a few buildings.     

An integrated object-based image analysis and CA-Markov model approach for modeling land use/land cover trends in the Sarab plain

The present paper is an attempt to integrate a semi-automated object-based image analysis (OBIA) classification framework and a cellular automata-Markov model to study land use/land cover (LULC) changes. Land use maps for the Sarab plain in Iran for the years 2000, 2006, and 2014 were created from Landsat satellite data, by applying an OBIA classification using the normalized difference vegetation index, salinity index, moisture stress index, soil-adjusted vegetation index, and elevation and slope indicators. The classifications yielded overall accuracies of 91, 93, and 94% for 2000, 2006, and 2014, respectively. Finally, using the transition matrix, the spatial distribution of land use was simulated for 2020. The results of the study revealed that the number of orchards with irrigated agriculture and dry-farm agriculture in the Sarab plain is increasing, while the amount of bare land is decreasing. The results of this research are of great importance for regional authorities and decision makers in strategic land use planning.