مطالب مرتبط با کلیدواژه

Regression


۱.

سنجش آسیب پذیری سازه ای بافت فرسوده شهری در برابر مخاطرات، با رویکرد پدافند غیر عامل (مطالعه ی موردی: بافت فرسوده مرکزی کلان شهر اهواز)(مقاله علمی وزارت علوم)

نویسنده:
منبع: سپهر دوره ۲۶ زمستان ۱۳۹۶ شماره ۱۰۴

کلیدواژه‌ها: آسیب پذیری سازه Regression بافت فرسوده Anselin Local Morans پدافند غیرعامل اهواز

حوزه‌های تخصصی:
تعداد بازدید : ۸۳۴ تعداد دانلود : ۴۴۱
امروزه در پی تغییرات سریع شهرها، بخشی از بافت های شهری به علت فرسودگی و ناکارآمدی نتوانسته اند ارتباطی مناسب با محیط خود و خدمات دهی به بهره برداران برقرار کنند. وجود سطح گسترده بافت فرسوده یکی از مهم ترین چالش های مدیران شهری، شهرسازان و معماران می باشد، زیرا عدم توجه به این بافت ها موجب زوال شهر و توسعه ناهمگون آن وایجاد شهرهایی نوپا در حاشیه شهر قدیمی می گردد. منطقه یک شهر اهواز به این علت که بخش قابل توجهی از مشکلات شهر اهواز در این منطقه نمود عینی یافته است و بخش مرکزی به دلیل گستردگی بیش از حد بافت فرسوده و روند  فرسودگی شدید در آن، به عنوان قلمرو مورد پژوهش انتخاب شد. پژوهش حاضر به لحاظ هدف توسعه ای- کاربردی و از لحاظ روش شناسی توصیفی- تحلیلی مبتنی بر مطالعات کتابخانه ای وبررسی های میدانی است. برای دستیابی به اهداف تحقیق، شاخص های اسکلت ساختمان، جنس مصالح، تعداد طبقات و قدمت ساختمان استخراج شد. برای کشف روند الگوها از ابزار Regression و برای وزن دهی به لایه ها در داده های فضایی از روش خود همبستگی فضایی موجود در نرم افزار Geoda استفاده شد. همچنین برای بررسی آسیب پذیری بافت فرسوده از روش ( [1]Aneslin Local Morans) از ابزار  sisylanA reiltuO & retsulC از مجموعه ابزارهای موجود در  slooT scitsitatS laitapS مربوط به نرم افزار  SIG crA استفاده شده است. نتایج این پژوهش نشان می دهد 38/54 درصد مساحت در بازه آسیب پذیری متوسط تا زیاد قرار دارد و گویای این است که بخش زیادی از بافت فرسوده در محدوده مرکزی شهر اهواز به نوعی نیازمند برنامه ریزی پدافند غیرعامل می باشد. [1]- انسلین محلی موران
۲.

Modeling Rainfall Erosivity Factor for Single Showers: A Case Study in Khuzestan Province, Iran(مقاله علمی وزارت علوم)

نویسنده:
منبع: The International Journal of Humanities, Volume ۱۳, Issue ۳ (۲۰۰۶) 41-50
تعداد بازدید : ۵۴۸ تعداد دانلود : ۲۶۰
This study tries to investigate relationship between rainfall parameters and USLE R factor. To gain R-factor, at first, shower kinetic energy was calculated and then its erosivity computed by using maximum 30 minutes rainfall intensity. Therefore 3 meteorological stations in Khuzestan province and one station per Kohgiloyeh & BoyerAhmad and Boushehr provinces were selected and their recorded hyetographs of 13 years were analyzed. For any hyetographs, rainfall erosivity was computed in any one month, season, or year and corresponding rainfall parameters were extracted too. Temporal and spatial variation of rainfall erosivity was studied and relationships between R factor and rainfall characteristics were investigated by using regression analysis. It was resulted that February to March and winter season has the most erosivity risk. Spatial analysis of rainfall erosivity in selected area showed that Dezful and Ramhormuz have the maximum erosivity factor. Mean annual erosivity factor of Khuzestan province was computed 28.07 ton.m/ha.h. Regression analysis showed strong relationships between rainfall amount (mm) and maximum 30 minutes rainfall intensity (cm/h) with R factor. A model that computes R-factor by means of rainfall amount was suggested.
۳.

Energy Demand Forecast of Iran’s Industrial Sector Using Markov Chain Grey Model(مقاله علمی وزارت علوم)

نویسنده:
منبع: The International Journal of Humanities, Volume ۲۰, Issue ۱ (۲۰۱۳) 1-12
تعداد بازدید : ۳۳۱ تعداد دانلود : ۲۵۴
The aim of this paper is to develop a prediction model of energy demand of Iran’s industrial sector. For that matter a Markov Chain Grey Model (MCGM) has been proposed to forecast such energy demand. To find the effectiveness of the proposed model, it is then compared with Grey Model (GM) and regression model. The comparison reveals that the MCGM model has higher precision than those of the GM and the regression. The MCGM is then used to forecast the annual energy demand of industrial sector in Iran up to the year 2020. The results provide scientific basis for the planned development of the energy supply of industrial sector in Iran.
۴.

Relationship between Family Functioning and Attitude towards Delinquency in Adolescents in Babol County(مقاله علمی وزارت علوم)

نویسنده:
منبع: Iranian journal of educational sociology, Vol ۱, Number ۱۰ (۲۰۱۸) 87-94

کلیدواژه‌ها: Family Functioning Delinquency adolescents Babol Regression

حوزه‌های تخصصی:
تعداد بازدید : ۳۹۳ تعداد دانلود : ۲۱۴
Purpose: The purpose of this study was to investigate the relationship between family functioning and attitude towards delinquency in adolescents. Methodology: The research method was correlational. The statistical population of the study included all high school students in Babol in the academic year of 2016-2017. Among them, 689 people (334 boys and 355 girls) were selected by cluster sampling method. The research tool was Fazli’s questionnaire for attitude towards delinquency and McMaster family functioning scale. The results of Pearson correlation coefficient showed that there is a negative and significant relationship between family functioning and its dimensions including problem solving, roles, communication, emotional attachment, emotional association, control, and attitude towards delinquency. Findings: The results of stepwise multivariate regression indicated that among the components of family functioning, only the component of roles explained the 0.03 of the variance of attitude towards delinquency. Conclusion: Based on the results of this research, it is suggested that in schools, family education programs should have emphasized the family psychological empowerment and promotion of family functioning. Family counselors should also work on counseling sessions and work with families to improve family functioning, in particular, component of roles.
۵.

Sustainability of Iranian Banks: Role of Financial and Non-Financial Determinants(مقاله علمی وزارت علوم)

نویسنده:
منبع: Journal of Money and Economy, Vol. ۱۴, No. ۴, Fall ۲۰۱۹ 495-524

کلیدواژه‌ها: Bank Sustainability Financial Determinants Regression

حوزه‌های تخصصی:
تعداد بازدید : ۳۰۳ تعداد دانلود : ۳۶۳
This study aimed to investigate the role of financial and non-financial determinants of the sustainability of Iranian banks. Accordingly, the sustainability score of 27 public and private Iranian banks were evaluated in 2017 by employing a sustainability model. The model was developed by the acquisition of sustainability codes, themes, and categories in the banking industry through Meta Synthesis, while its casual structure was determined by a combined method of Interpretive Structural Modeling and Analytical Network Process. Subsequently, we calculated the sustainability scores by using our proposed model to analyze the content of the banks’ disclosed information. Then, the effect of capital adequacy, total assets, financial leverage, loan to deposit ratio, return on assets and number of branches were investigated using multiple regressions on the banks' sustainability scores. Findings depict that total assets have a positive and significant relationship and capital adequacy has a negative and significant relationship with a bank's sustainability. Therefore, banks with more assets are more willing to participate in sustainability activities, due to more appropriate financial resources, as well as to support the bank's brand and its reputation to stakeholders. On the other hand, due to the wrong belief that sustainability is costly, and non-value adding for the banks, they get less involved in order to increase their capital adequacy ratio.
۶.

Performance of Building Energy Efficiency by Orientation with Regression (Case study: Semi Desert in Iran)(مقاله علمی وزارت علوم)

نویسنده:
منبع: Architecture and Urban Development, Volume ۶, Issue ۲ - Serial Number ۲۰, Spring ۲۰۱۶ 15 - 22

کلیدواژه‌ها: Energy consumption Solar Radiation Residential sector Building orientation Cooling need Regression

حوزه‌های تخصصی:
تعداد بازدید : ۳۳۸ تعداد دانلود : ۱۲۴
In this research multiple-regression analysis with stepwise selection method was employed for investigating the effect of vertical building envelopes solar radiation (Evr) on cooling energy consumption (E cooling) in residential sector. The high capacity of solar energy in semi-arid climate (Shiraz) can provide a part of buildings required energy. Depends on house orientations in two directions of SE and SW and by using statistical data, E cooling in urban residences was analyzed. The autocorrelation in the residuals, checked by Durbin- Watson test, was not existed. By investigating the relations between average Evr and E Cooling in each group, it can be proved that climatic orientated houses can achieve lower E Cooling, owing to SE desirable orientation. The percentage of Evr in SW houses is 28.89 % and in SE it is 15.72 %, so choosing the building orientation is important to reduce energy consumption. Finally, the concluding remarks were indicated.
۷.

Comparison of the Ability of Modern and Conventional Metaheuristic and Regression Models to Predict Stock Returns by Accounting Variables and Presenting an Effective Model(مقاله علمی وزارت علوم)

نویسنده:
منبع: Advances in Mathematical Finance and Application, Volume ۷, Issue ۲, Spring ۲۰۲۲ 447-466

کلیدواژه‌ها: Prediction of Stock Returns Metaheuristic Models Neural Network Regression

حوزه‌های تخصصی:
تعداد بازدید : ۲۵۲ تعداد دانلود : ۱۶۵
Investment in the stock market requires decision-making and access to infor-mation on the future of the stock market. Given the importance of predicting stock returns, the present study aimed to discover the variables and indices that could predict stock returns. The prediction of stock returns has long been a 'hot topic' in advanced countries. While effective steps have been taken in this regard, the accu-rate prediction of stock returns remains a problem due to numerous issues. In this study, an accurate, applicable, and effective model was proposed for the predic-tion of stock returns. The statistical sample included 138 active companies of Tehran Stock Exchange (TSE) during 2008-2017, which were selected by the systematic removal method. In total, 1,380 data years were selected for the re-search to evaluate the questions. Data analysis was performed using an adaptive neuro-fuzzy inference system (ANFIS), multi-gene genetic programming, and regression analysis. In addition, statistical tests were applied to evaluate the accu-racy of the model, implemented by MATLAB and GeneXproTools. According to the results, the hybrid metaheuristic method had a lower error rate compared to artificial neural network and regression analysis in terms of stock return predic-tion. Therefore, the proposed model could provide more accurate data within a shorter time to predict the stock market status since it makes predictions after selecting the most optimal input variables through ANFIS.