مدل‌سازی

Open Access Article

1 - Fuzzy Evaluation of Long-Term Impacts of Electrical Appliances Efficiency Improvement on Load Pattern
M. Behrangrad M. Parsa-Moghaddam

20.1001.1.16823745.1386.5.12.8.9

Evaluation of long-term home electrical appliance efficiency improvement scenarios on load and energy pattern needs comprehensive and precise modeling taking to account a variety of uncertainties. In the modeling process, all effective parameters should be considered. E More

Evaluation of long-term home electrical appliance efficiency improvement scenarios on load and energy pattern needs comprehensive and precise modeling taking to account a variety of uncertainties. In the modeling process, all effective parameters should be considered. Estimation is the main source of information in this process which is a long-term large scale impact assessment procedure. Furthermore, the non homogeneous structure of load behavior in response to DSM policies makes the problem more sophisticated. The presented method implies fuzzy numbers to model the main uncertainties of the demand side reactions to the proposed DSM program. Here, the social classes of customers and their behaviors regarding energy utilization as well as time dependency of the problem parameters are taken into account. The paper focuses on the efficiency improvement of the electric appliances in Iran as a long-term DSM program, due to their considerable share in electricity consumption in residential sector. Finally, the numerical results are presented. Manuscript profile

Open Access Article

2 - Experimental Modeling of Two-Dimensional Systems with ARMA Structure
M. sadabadi M. shafiee M. karrari

20.1001.1.16823745.1388.7.17.9.4

In this paper, experimental modeling of two-dimensional discrete systems with ARMA structure is considered. Therefore two-dimensional model order selection and parameter estimation problems are proposed. This method shows that the information of AR and MA orders are imp More

In this paper, experimental modeling of two-dimensional discrete systems with ARMA structure is considered. Therefore two-dimensional model order selection and parameter estimation problems are proposed. This method shows that the information of AR and MA orders are implicitly contained in two different correlation matrices and the AR and MA orders of the 2-D ARMA model can be independently determined before parameter estimation. The two-dimensional model is assumed to be causal, stable, linear, and spatial shift-invariant with quarter plane (QP) support. Numerical Simulations are presented to show the good performance and effectiveness of the proposed method in two-dimensional discrete system with ARMA structure. Manuscript profile

Open Access Article

3 - A New Approach for Modeling and Global Optimum Solution of Transmission Expansion Planning Including Contingency Conditions
A. Nateghia H. Seifi Mohammad Kazem Sheikh El Eslami S. M. Sepasian

20.1001.1.16823745.1391.10.1.1.5

ts cause different neural responses containing a regular firing, or a long latency before firing with or without a leading spike. In this paper, the firing behavior of DCN pyramidal cells is simulated first Transmission Expansion Planning (TEP) is an important issue of More

ts cause different neural responses containing a regular firing, or a long latency before firing with or without a leading spike. In this paper, the firing behavior of DCN pyramidal cells is simulated first Transmission Expansion Planning (TEP) is an important issue of power system planning studies. In literature, different methods are investigated to achieve good solutions for TEP. This paper uses Mixed Integer Linear Programming (MILP) and Mixed Integer Nonlinear Programming (MINLP) methods to study TEP. It also presents a new NLP model in which the integer variables are omitted. Moreover, the models are properly modified so that contingency conditions are also observed. Different combinations of cost functions such as the expansion cost, the operation cost and the cost of the losses are considered and compared. To reach a global optimum solution, BARON solver is applied. The proposed algorithm is applied on Garver 6-bus and IEEE-118 bus test systems. It is shown that modeling the problem by MINLP and NLP methods, in combination with a proper solver, can result in a quick optimum solution. Manuscript profile

Open Access Article

4 - Simulation of Pyramidal Cells Firing Types and Adjustment of Their Characteristics by Means of Transient Potassium Currents
Z. Daneshparvar M. R. Daliri

20.1001.1.16823745.1391.10.1.2.6

Pyramidal cells of the dorsal cochlear nucleus (DCN) represent firing types with different latencies. They incorporate two transient potassium currents namely Ikif and Ikis with fast and slow inactivation gatings, respectively. Transient potassium currents i.e. currents More

Pyramidal cells of the dorsal cochlear nucleus (DCN) represent firing types with different latencies. They incorporate two transient potassium currents namely Ikif and Ikis with fast and slow inactivation gatings, respectively. Transient potassium currents i.e. currents having both activation and inactivation gatings influence on the latency before firing. These currents cause different neural responses containing a regular firing, or a long latency before firing with or without a leading spike. In this paper, the firing behavior of DCN pyramidal cells is simulated first with a 3-variable conductance-based model. Next, mechanisms underlie neural responses of the model are analyzed by dynamical systems analysis methods. The model is a reduced version of Kanold and Manis model with 10 variables. Manuscript profile

Open Access Article

5 - Implementation of a Fuzzy Multi-Agent Model for City Evacuation Traffic Management Using Probabilistic Automata
A. R. Karbaschian Saeed Setayeshi arash Sharifi

20.1001.1.16823745.1393.12.4.3.7

Because of importance of quickly city evacuation during natural or unnatural happenings, it’s essential to apply an optimized control policy to prevent congestion and stop of vehicles. Existing works for traffic management in critical conditions have paid little attenti More

Because of importance of quickly city evacuation during natural or unnatural happenings, it’s essential to apply an optimized control policy to prevent congestion and stop of vehicles. Existing works for traffic management in critical conditions have paid little attention to artificial intelligence approaches. Therefore, the main goal of authors in this research is offering an optimized and intelligent control policy for city evacuation traffic. This policy uses fuzzy inference system for decision making of each agent and probabilistic automata for optimizing performance of agents as for their preferences during time. To check degree of success of offered control policy, Agent Base Simulation in RStudio and Netlogo environments have been implemented using RNetlogo and frbs packages in R language. Simulation results show traffic load distribution, using maximum capacity of roads and congestion prevention by suggested policy. With regard to communication technologies such as GPS, smart phones, automatic tax payment systems in roads and … that have been developed in recent years, it is also possible to implement suggested critical traffic control policy in real world. Manuscript profile

Open Access Article

6 - Analyzing and Designing a Domain Specific Language to Describe Structure and Movement of Linkages
A. nourollah N. Behzadpour

20.1001.1.16823745.1397.16.2.2.0

This research has been prepared in the field of linkage structures and their movements. A linkage is a set of line segments that can be interconnected via their ends, which exhibits numerous usages in modeling robot arms. To date, various domain-specific languages have More

This research has been prepared in the field of linkage structures and their movements. A linkage is a set of line segments that can be interconnected via their ends, which exhibits numerous usages in modeling robot arms. To date, various domain-specific languages have been introduced in the field of robot movements. In spite that some of the capabilities of these languages combined with general-purpose languages can be used to describe and create the movements of these linkages and their structures, yet they cannot be considered domain-specific languages for explaining the linkages and their movements. The domain-specific languages are programs that raise the level of abstraction, the ability to understand better, accelerating the development and requires less effort to learn relevant knowledge that will provide the same advantages. So like all software, have levels such as analysis, design, implementation, testing, maintenance and support. Therefore, in this paper, we attempt to analyze and design a domain-specific language and describe and create linkage movements and their structures. By using this domain specific language, there is no limit to the definition of simple linkages in terms of it’s number. Also, by defining the modules and their sequential and parallel combinations, the final movements of the linkages are generated, and by using the features of the language, the terms needed to start or terminate each final movements are defined. Applying this kind of attitude to specific general-purpose modeling, in addition to providing ease in defining the structure of linkages and diversity in their initial definition, allows for the coordination and collaboration of multiple robots to perform a single task and then implemented in the next step. Manuscript profile

Open Access Article

7 - Winding Losses Calculation in Multi-Winding Traction Transformer Using a Semi-Numerical Method
D. Azizian G. Gharehpetian

20.1001.1.16823745.1397.16.4.4.6

Nowadays, multi-winding transformers are widely used in power systems, especially in traction networks and steel producing companies. The multi-winding transformers have special geometry. They encounter with serious problems and difficulties in design procedure in compa More

Nowadays, multi-winding transformers are widely used in power systems, especially in traction networks and steel producing companies. The multi-winding transformers have special geometry. They encounter with serious problems and difficulties in design procedure in comparison with conventional two-winding transformers. Considering the importance of windings losses (and the generated heat), the current research firstly focuses on thermal calculations in this type of transformers, also introduces a semi-numerical technique for electromagnetic analysis of split-winding traction system transformer. Combining finite element and analytical methods, the windings losses distribution due to eddy currents is calculated and the modeling results are validated using the experimental results. As shown, the introduced semi-numerical method is a powerful technique for electromagnetic modeling and winding losses calculations in split-winding transformers. Also, the winding losses of the split-winding transformer are discussed and compared to the conventional two-winding transformer results. Finally, the relation between the winding losses and frequency is studied in this paper. Manuscript profile

Open Access Article

8 - Probabilistic Modeling of Fast Charging Station Load Demand for Public Electric Vehicles
Hossein Yousefi Meghdad Tourandaz Kenari Mohammad Sadegh Sepasian

20.1001.1.16823745.1398.17.1.5.8

Considering economic and environmental factors, it is expected that the number of plug-in electric vehicles (PEVs) will be increased, rapidly. The high penetration of EVs, can affect the power system. Therefore, in recent years, various studies have paid their attention More

Considering economic and environmental factors, it is expected that the number of plug-in electric vehicles (PEVs) will be increased, rapidly. The high penetration of EVs, can affect the power system. Therefore, in recent years, various studies have paid their attention to the impacts of PEVs charging on the network. In this paper, a probabilistic model based on the queueing theory is extracted using Monte Carlo simulation for modeling EV charging station load. It is assumed that the vehicles are the taxis of Amol city in Mazandaran province. Required data such as the time of arrival and the state of charge of the battery before charging, were collected and extracted using three methods from intra-city taxis in the city of Amol. To obtain the demand load of EV charging, the traffic-based behavior of drivers is needed. This behavior is stochastic. Therefore, its related variables will not be deterministic and must be evaluated using probabilistic methods. Manuscript profile

Open Access Article

9 - Modeling of K-250 Compressor Using NARX and Hierarchical Fuzzy Model
Adel Khosravi Abbas Chatraei G. Shahgholian Seyed-Mohamad Kargar

20.1001.1.16823745.1399.18.3.2.6

Due to the increasing use of compressors in the industry, it is important to determine a mathematical model for the compressor to design a control system, analysis and simulation of the computer. Also, in recent years, smart modeling such as neural network and fuzzy net More

Due to the increasing use of compressors in the industry, it is important to determine a mathematical model for the compressor to design a control system, analysis and simulation of the computer. Also, in recent years, smart modeling such as neural network and fuzzy network have been considered by researchers for their more realistic performance, and their types have been used for modeling. Smart methods have high capability to communicate between input and output data. In this paper, modeling of K-250 compressor at Isfahan smelter company based on smart models of fuzzy neural network is presented. The Nonlinear Auto Regressive With exogenous input (Narx) and hierarchical fuzzy network are presented. For modeling, the system has been tested and the input and output data of the compressor using compressor sensors and image processing are used to convert the data into the required data in the modeling, then the above algorithms of the compressor model will be achieved with the help of software, MATLAB. The results of modeling Which NARX performed better than hierarchical fuzzy. Among the two models presented in this paper, the NARX model shows a better response than the hierarchical fuzzy network in all cases and in all aspects of the performance criteria. Manuscript profile

Open Access Article

10 - Calculation of the Dimensions and Speed of the Car from the Video Received from the Uncalibrated Camera
R. Asgarian Dehkordi H. Khosravi

20.1001.1.16823745.1398.17.2.11.6

In this paper, a fully automated method for calibrating the camera and obtaining dimensions and speed of vehicles is presented. In this method, at first, vanishing points and the focal length of the camera are obtained, according to the directions of the cars in the ini More

In this paper, a fully automated method for calibrating the camera and obtaining dimensions and speed of vehicles is presented. In this method, at first, vanishing points and the focal length of the camera are obtained, according to the directions of the cars in the initial frames. After detecting moving vehicles, their 3D bounding box are created using the vanishing points. In order to deal with the perspective, the bounding box of each vehicle is projected on a hypothetical road and then to have their real dimensions in meter, the metric coefficient (pixel-to-meter conversion) is obtained. This calculates the coefficient; a dominant car is detected and according to its metric dimensions, the pixel to meter coefficient is computed. Projecting the vehicle on the road surface and the use of the metric coefficient provides the possibility of expressing the actual speeds and dimensions of the vehicles in each frame. However, it may have some errors. To increase the accuracy of the results, these parameters are aggregated along the vehicle's path, and some histograms are made up for the speed and dimensions of each vehicle. Then the maximum of these histograms is reported as new values of speed and dimensions for each vehicle. This will improve the accuracy. Creating histograms for each vehicle requires tracking of the car in multiple frames. For this purpose, a fast algorithm is presented. Comparing the results of the proposed method with previous methods indicates higher processing speed and better response. The average error of dimension estimation is 1.4%, and the error of speed estimation is 1.1 km/h. The average processing speed for testing videos in MATLAB is about 3.5 frames per second. Manuscript profile

Open Access Article

11 - Resource Management in Multimedia Networks Using Software-Defined Network Technology
Ahmadreza Montazerolghaem

20.1001.1.16823745.1401.20.1.2.6

Nowadays, multimedia networks on the Internet have become a low-cost and efficient alternative to PSTN. Multimedia transfer applications on the Internet are becoming more and more popular. This connection consists of two phases: signaling and media. The signaling phase More

Nowadays, multimedia networks on the Internet have become a low-cost and efficient alternative to PSTN. Multimedia transfer applications on the Internet are becoming more and more popular. This connection consists of two phases: signaling and media. The signaling phase is performed by SIP proxies and the media phase by network switches. One of the most important challenges in multimedia networks is the overload of SIP proxies and network switches in the signaling and media phases. The existence of this challenge causes a wide range of network users to face a sharp decline in the quality of service. In this article, we model the routing problem in multimedia networks to deal with the overload. In this regard, we present a technology-based method of software-based networks and a mathematical programming model in multimedia networks. The proposed method is simulated under various scenarios and topologies. The results investigate that the throughput and resource consumption has improved. Manuscript profile

Open Access Article

12 - Spatio-Temporal Prediction of Vegetation Dynamics Based on Remote Sensing Data Using Deep Learning
Elham Zangeneh H. Mashayekhi Saeed Gharachelo

20.1001.1.16823745.1401.20.4.2.2

Understanding and analyzing spatial-temporal data changes is very important in various applications, including the protection and development of natural resources. In the past studies, Markov process and comparison-based methods were mainly used to predict the changes o More

Understanding and analyzing spatial-temporal data changes is very important in various applications, including the protection and development of natural resources. In the past studies, Markov process and comparison-based methods were mainly used to predict the changes of vegetation indices, whose accuracy still needs improvement. Although time series analysis has been used to predict some indices, the method to extract these indices from remote sensing data and model their sequences with deep learning is rarely observed. In this article, a method for predicting changes in plant indices based on deep learning is presented. The research data includes Landsat satellite images from 2000 to 2018, related to four seasons in the north and east of Shahrood city in Semnan province. The time span of the extracted images makes it possible to predict changes in vegetation cover. Vegetation indices extracted from the data set are NDVI, SAVI and RVI. After performing atmospheric corrections on the images, the desired indicators are extracted and then the data is converted into a time series. Finally, the modeling of the sequence of these data is performed by the Short-Long-Term Memory (LSTM) network. The results of the experiments show that the deep network is able to predict future values with high accuracy. The amount of the model error without additional data is 0.03 for the NDVI index, 0.02 for the SAVI index, and 0.06 for the RVI index. Manuscript profile

Open Access Article

13 - Modeling of Solar Power Plant Using a Neural Network Based on the Equivalent of a Single Diode
Ali Reza reisi Rohollah Abdollahi

<p style="padding-right: 30px; text-align: justify;"><!-- [if gte mso 9]><xml> <w:WordDocument> <w:View>Norma More

<p style="padding-right: 30px; text-align: justify;"></p> <p class="Abstract" style="padding-right: 30px; text-align: justify;"><span style="mso-bidi-font-weight: normal;">Various methods have been proposed for modeling solar panels, but modeling solar power plants using them is associated with challenges. In equivalent circuit-based methods, the modeling depends on factory data that changes over time. Modeling of voltage-current characteristic using intelligent methods such as neural network was less considered due to the low accuracy of modeling. In this article, a method independent of the manufacturer's data for modeling the solar power plant is presented, so that it is possible to accurately model the solar power plants that have been installed for several years. The proposed method consists of two steps, in the first step, open circuit voltage, maximum power point and short circuit current are modeled according to atmospheric conditions using neural network. In the second step, the unknown parameters of the equivalent circuit are determined by circuit analysis relations and using neural network outputs. Finally, to evaluate the proposed method, a 3-kW solar power plant was modeled, and the results show the appropriate accuracy of the proposed method for modeling the solar power plant.</span></p> <p style="padding-right: 90px; text-align: justify;"> </p> Manuscript profile

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