محاسبات نرم در علوم مهندسی: 2 (1)

Open Access Article

1 - Comparison of Artificial Neural Network and Regression Methods in Predicting the Modulus of Deformation of Stone using Dilatometry Test.
Manouchehr Hoseine Rouzbeh Dabiri Larissa Khodadadi

In geotechnical engineering, the modulus of deformation (Em) is actually the ratio of stress to strain. The application of this module is in the fields of dam construction, tunnel construction, road construction, etc. Today, there are various methods to obtain the defor More

In geotechnical engineering, the modulus of deformation (Em) is actually the ratio of stress to strain. The application of this module is in the fields of dam construction, tunnel construction, road construction, etc. Today, there are various methods to obtain the deformation modulus, among which we can refer to in-situ tests (loading plate-dilatometry), laboratory tests, and practical relationships. Also, there are different methods to predict and determine the relationships between several different parameters, which can be referred to regression analysis and artificial neural network. The main goal of the present research is to provide a new relationship to predict the modulus of deformation of rocks before performing the dilatometry test with the least error. The results of the studies have shown that neural network modeling is more efficient than regression analysis in all input independent variables, and it has a higher level of confidence only with the input of Q parameter to the regression analysis equation. Also, by comparing these two methods, it was found that the more the number of input variables, the better the neural network works. Manuscript profile

Open Access Article

2 - The numerical investigation of the weak clay soil treatments using vacuum preloading and vertical drains without embankment surcharge
mehdi mokhberi Mohammad Mehdi Pardsouie mehdi momeni roghabadi

Due to the fast growth of urban and industrial facilities, the necessity of construction in new land becomes inevitable. Most of these lands were left as a result of the existence of weak layers that make them unsuitable for construction. One the methods in treatment of More

Due to the fast growth of urban and industrial facilities, the necessity of construction in new land becomes inevitable. Most of these lands were left as a result of the existence of weak layers that make them unsuitable for construction. One the methods in treatment of such lands that have weak clay layers is the application of surcharge with or without prefabricated vertical drains or vacuum. In this literature first a brief description of the vacuum and surcharge preloading is presented and then a case history was investigated by finite element method that consists of only vacuum and prefabricated vertical drains without embankment. Based on the results the application of vacuum preloading alone even in the absence of surcharge, would give satisfactory results, especially where the application of surcharge preloading is not possible due to the unavailability of suitable loading material or the existence of sensitive buildings or infrastructures. The results of this literature can be used by consulting companies or personals who are active in land reclamation, especially in offshore regions. Manuscript profile

Open Access Article

3 - Site Selection for Temporary Housing after Earthquake in Kerman City Using Multi-Criteria Decision Making Methods
Shahram Ariafar Fatemeh Shojaei

Worldwide every year, many people lose their lives and their homes due to natural disasters. Providing appropriate places for establishment of relief centers and resettling displaced people after an earthquake is one of the most important things in planning and crisis m More

Worldwide every year, many people lose their lives and their homes due to natural disasters. Providing appropriate places for establishment of relief centers and resettling displaced people after an earthquake is one of the most important things in planning and crisis management. In this article, the city of Kerman has been selected and studied due to its high earthquake potential, in order to locate temporary settlements for the population affected by a possible earthquake. To do so, initially, three potential sites for temporary accommodation and effective criteria to rank them were identified. Afterward, the weights of the criterion were determined using the Analytical Hierarchy Process (AHP), and finally, sites were prioritized using TOPSIS and VIKOR methods. Based on the results access to main routes, access to rescue centers, the possibility of installing infrastructure facilities, and the size of the selected site gained respectively the most to least weights. Further, among suggested locations, Madar Park was ranked first. Manuscript profile

Open Access Article

4 - Possibility of the Economic Prediction Model based on the Smart Algorithm of the Smart City
mahsa khodadadi Larissa Khodadadi روزبه دبیری

Smart cities make better use of space and have less traffic, cleaner air and more efficient city services and improve people's quality of life. The large number of vehicles that are constantly moving through congested areas in smart cities complicates the availability o More

Smart cities make better use of space and have less traffic, cleaner air and more efficient city services and improve people's quality of life. The large number of vehicles that are constantly moving through congested areas in smart cities complicates the availability of a public parking space. This creates challenges for both traffic and residents. With such a large population, road congestion is a serious challenge. It wastes vital resources like fuel, money and most importantly time. Finding a suitable place to park is one of the reasons for traffic jams on highways. This paper proposes an economic forecasting model based on deep learning for long-term economic growth in smart cities. Traffic management is vital for cities in that it ensures that people can move freely around the city. Many cars trying to reach congested areas in smart cities make it difficult to find a public parking lot. This issue is inconvenient for both drivers and residents. A number of traffic management authorities have implemented an artificial neural network to solve this problem, and modern car systems have come with smart parking solutions. The experimental result of the economic forecasting model based on deep learning improves traffic estimation, accurate prediction of traffic flow, traffic management and intelligent parking compared to existing methods Manuscript profile

Open Access Article

5 - Precipitation-runoff Simulation with Neural Network(Case study: Nasa Bam Plain)
mehdi shahrokhi sardoo mojtaba jafari kermanipour

Short-term runoff forecasting is of particular importance due to its direct relationship with how managers interact with life risks caused by floods. In this research, by using artificial neural networks, simulation of rainfall-runoff process has been done on a daily ba More

Short-term runoff forecasting is of particular importance due to its direct relationship with how managers interact with life risks caused by floods. In this research, by using artificial neural networks, simulation of rainfall-runoff process has been done on a daily basis in the Nasa Bam watershed. In order to predict the future process of using the water resources of the mentioned plain, different combinations of rainfall and temperature data and discharge and discharge difference of two consecutive days were used. The number of hidden layer neurons in the neural network varied between 2 and 10 neurons. The statistical criteria of root mean square error RMSE, mean absolute value of error MAE and correlation coefficient R were used to evaluate and compare the performance of neural networks in runoff forecasting. The results showed that by having 2 inputs and feedforward neural network or 1 input and newrbe network, the best performance was achieved and the rainfall-runoff process was predicted with higher accuracy. Manuscript profile

Open Access Article

6 - Determining the location of Temporary Housing for Earthquake Victims in Kerman City Using Multi-Criteria Decision-Making Methods
Shahram Ariafar Fatemeh Shojaei

Worldwide every year, many people lose their lives and their homes due to natural disasters. Providing appropriate places for the establishment of relief centers and resettling displaced people after an earthquake is one of the most important things in planning and cris More

Worldwide every year, many people lose their lives and their homes due to natural disasters. Providing appropriate places for the establishment of relief centers and resettling displaced people after an earthquake is one of the most important things in planning and crisis management. In this article, the city of Kerman has been selected and studied due to its high earthquake potential, in order to locate temporary settlements for the population affected by a possible earthquake. To do so, initially, three potential sites for temporary accommodation and effective criteria to rank them were identified. Afterward, the weights of the criterion were determined using the Analytical Hierarchy Process (AHP), and finally, sites were prioritized using TOPSIS and VIKOR methods. Based on the results access to main routes, access to rescue centers, the possibility of installing infrastructure facilities, and the size of the selected site gained respectively the most to least weights. Further, among suggested locations, Madar Park was ranked first. Manuscript profile

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