فیلتر کالمن

Open Access Article

1 - Dynamic Efficiency in Tehran Stock Exchange by Kalman Filter
Zahra Farshadfar Marcel Prokopczuk

Estimating informative efficiency in financial market is crucial for investors. They can gain unusual profit when the market is inefficient. As informative efficiency is evolving and undergoing changes in emerging markets such as Iran, classic methods for efficiency est More

Estimating informative efficiency in financial market is crucial for investors. They can gain unusual profit when the market is inefficient. As informative efficiency is evolving and undergoing changes in emerging markets such as Iran, classic methods for efficiency estimation in these kind of financial markets are not suitable. Therefore, in such markets a hybrid method needs to be applied in such a way that the existing status of efficiency (static approach) and the efficiency during time (dynamic approach- in the absence of static efficiency) can be studied. The present study aims to determine the efficiency of Tehran Stock Exchange market by both static and dynamic approach. In order to obtain this goal, a combination of TVPGARCH and Kalman filter methods were applied on weekly total price index data during 2008 to 2017. Results indicate that the performance in Tehran Stock Exchange market in the static form does not have week efficiency. On the other hand, there is no evidence of efficiency dynamicity in Tehran Stock Exchange market performance during the studied period. Manuscript profile

Open Access Article

2 - Smart Portfolio Modeling Using the Kalman Filter Pattern and Kelly Functions
Reza Mansourian Nader Rezaei Seid Ali Nabavi Chashmi Ahmad Pouyanfar Ali Abdollahi

The purpose of this study is to present a model for executing smart financial portfolios using Kalman filter model and kelly functions. For this purpose, using the monthly data of 180 companies listed in Tehran Stock Exchange during the period 2013 to 2019, using the Ka More

The purpose of this study is to present a model for executing smart financial portfolios using Kalman filter model and kelly functions. For this purpose, using the monthly data of 180 companies listed in Tehran Stock Exchange during the period 2013 to 2019, using the Kalman filter model and kelly functions, the Sharp ratio is improved and the intelligent method for trading based on momentum and capital algorithms Long-term stock listing was presented and the purpose of the study was examined. The results of the algorithms implementation confirm that the proposed structure of the intelligent model of kelly functions is better in terms of average efficiency and Sharp ratio than the quantitative investment algorithms and it is possible to use the general constellation in optimal allocation of resources to achieve more desirable results. Finally, the results indicated that the performance of the smart portfolio with the kelly functions algorithm is better than the momentum model and long-term investment. Manuscript profile

Open Access Article

3 - برآورد شکاف تولید در ایران و بررسی تاثیر شوک های نفتی بر آن
مریم خوشنویس افسانه هادیخانی

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Open Access Article

4 - Estimated the potential added value in major economic sectors of Iran with Kalman filter
کامبیز هژبر کیانی محمد نقیبی

The role and the knowledge of measures of Potential Output in policy analysis are of significant importance in Macroeconomics. The aim of this paper is to use the production function approach in order to measure Potential Output through state-space Model, Kalman filter More

The role and the knowledge of measures of Potential Output in policy analysis are of significant importance in Macroeconomics. The aim of this paper is to use the production function approach in order to measure Potential Output through state-space Model, Kalman filter method. To achieve this goal, we have estimated the value added output of mining, construction, oil and gas, agriculture, water and electricity, and service industries during 1339 – 1389in Iran. Manuscript profile

Open Access Article

5 - comparative study of dynamic performance of investment according to method (garch)and kalman filter
Javad Yousefi Brahman JAVAD ramezani Mehdi Khalilpour

The importance of investing for economic growth and development is enough to make it a strong incentive to reach development; one that investors care about is the information that comes from the coming part of the company.In spite of an efficient construction of the mar More

The importance of investing for economic growth and development is enough to make it a strong incentive to reach development; one that investors care about is the information that comes from the coming part of the company.In spite of an efficient construction of the market, it is possible to identify companies and projects. one of the main parts of the capital market is the stock exchange. and efficiency is the main and most important feature of the stock exchange. according to the significant effect of efficiency on the trade and investment level, the main purpose of this study is to compare the dynamic performance of investment according to the garch and kalman filter method.in this research , by using kalman filter , the beta - kalman filter is applied to the firms listed in tehran stock exchange ( tse ) . then beta values for these shares are estimated using garch method and the efficiency of these two methods is compared .tthe results are obtained and based on the mean square error of each method , it can be stated that kalman filter method outperforms the garch method and therefore outperforms the garch model . Manuscript profile

Open Access Article

6 - The profitability of pairs trading strategy based on linear state-space models and the Kalman filter in Tehran Stock Exchange
Mohammad mehdi barahimipour sayyed mohammad reza davoodi

Statistical arbitrage as one of the subsets of algorithmic trading refers to strategies that employ some statistical model or method to take advantage of what appears to be mispricing between assets while maintaining a level of market neutrality. One of these strategies More

Statistical arbitrage as one of the subsets of algorithmic trading refers to strategies that employ some statistical model or method to take advantage of what appears to be mispricing between assets while maintaining a level of market neutrality. One of these strategies is pair trading that implements on two related long-term(co-integration) financial assets. The pair trading strategy of the research is based on the description of the visible process, the remainder of the co-integration model in terms of an invisible mean reverting process. This representation is in a state-space model and solved by the Kalman filter approach and the time of buying and selling is calculated in terms of two probabilities of growth and fall. The profitability of pair trading strategy on 21 stocks from oil product index and basic metal index of Tehran Stock Exchange between 1390-1395 was evaluated according to return and Sharp ratio. The results of the research show that the research method has the daily returns of 0.0048 and Sharp 1.23, which is more profitable in comparison with the pair trading based cointegration and market performance but the average daily its return is in the second place after the co-integration method. Manuscript profile

Open Access Article

7 - Impact of macroeconomic variables on unobserved systematic risk using Kalman filter
Majid Hatef Vahid Abbas Saleh Ardestani

The main purpose of this study was to investigate the effect of macroeconomic variables on unobserved systematic risk using the Kalman filter. Systematic risk indicates the degree of dependence between changes in share prices and changes in the market index. However, th More

The main purpose of this study was to investigate the effect of macroeconomic variables on unobserved systematic risk using the Kalman filter. Systematic risk indicates the degree of dependence between changes in share prices and changes in the market index. However, the amount of systematic risk can be very different from the expected amount, due to the confusion in stock price changes, resulting from emotional transactions, overreactions and price manipulation. Therefore, it is necessary to control the effects of these disturbances in measuring systematic risk. The method of the present study is descriptive-correlational which was performed using statistical methods to examine the relationships between variables based on Ives software. To analyze the data in this study, it is suggested to use Kalman filter. Also, filtered and turbulent values have been used under the heading of unobserved systematic risk. According to the obtained result, it can be said that all variables have a significant relationship with the systematic risk not observed in the model. Then, using data analysis, the hypotheses were examined. The results obtained in relation to statistics and a significant level show the confirmation of all hypotheses in terms of the impact of economic variables on the components of inflation, economic growth, exchange rate, stock market index and volume. Money showed unprecedented systematic risk. Also, the effect of different variables and finally the estimation of coefficients showed that the highest coefficient among the variables is related to inflation index and stock market. Manuscript profile

Open Access Article

8 - Virtual sensor design temperature for a dryer using a Kalman filter
arman khaleghi Morteza Mohammadzaheri Hadi Kargar Sharif Abad

This paper aims at introduction, design and validation of a temperature virtual sensor for an infrared dryer. As proposed in this article, a virtual sensor is an algorithm to estimate the temperature at one or some points in a thermal system (e.g. an infrared dryer) bas More

This paper aims at introduction, design and validation of a temperature virtual sensor for an infrared dryer. As proposed in this article, a virtual sensor is an algorithm to estimate the temperature at one or some points in a thermal system (e.g. an infrared dryer) based on the measured temperature at a number of other points. In this research, the designed algorithm estimates the temperature of a single point; however, the methodology can be evidently extended to multiple points.  Inspired by direct and inverse heat transfer models, a mathematical model is presented for virtual sensing. In the present study, we sensors that report temperature drying are performed, with the help of MATLAB and using a Kalman filter with an alternative estimator algorithm. First dryer with equipment in the lab was built and all the various trials that it was necessary to obtain data on the device. Mathematical models in state-space system were defined and then the least-square algorithm in MATLAB matrix coefficients of the equation of state of the system was identified. Then we just supposed to remove a thermocouple. The obtained model was used for planning the optimal Kalman filter. Next, remove the thermocouple temperature was estimated by the Kalman filter. Compare the actual temperature measured by the temperature and time of desired precision thermocouple measurement algorithms as well as Virtual temperature indicated. Manuscript profile

Open Access Article

9 - Sensorless Estimation of Battery Internal Temperature Using Dual Extended Kalman Filter
Mohseh Gholamrezaei Mohammad Toloo Askari

Abstract: The conventional approaches for estimating internal battery temperature use numerical electric-thermal models in which a temperature sensor is required. In order to ensure safe and proper use of lithium-ion batteries during operation, accurate estimation of ba More

Abstract: The conventional approaches for estimating internal battery temperature use numerical electric-thermal models in which a temperature sensor is required. In order to ensure safe and proper use of lithium-ion batteries during operation, accurate estimation of battery temperature is very important. In this paper, a method for estimating the surface and core temperature of the battery cell is presented using a coupled thermal model with an electrical impedance model without direct measurement of surface temperature. For this purpose, a dual extended Kalman filter (DEKF) consisting of a reduced thermal model along with battery current, voltage and impedance measurement can accurately estimate the temperature of the battery surface and core. The performance of the method is demonstrated experimentally on a 2.3-Ah lithium-ion iron phosphate cell fitted with surface and core thermo-couples for validation. The performance of the method is demonstrated experimentally on a 2.3-Ah lithium-ion iron phosphate cell fitted with surface and core thermo-couples for validation Manuscript profile

Open Access Article

10 - Optimal Observer Path Planning in Tracking Two Targets Using Side Angle Measurements
S.Ehsan Razavi Parastoo Poursoltani Naser Pariz

Multi-target tracking is considered to be a significant issue in various areas of monitoring, supervision, and updated communication services. It is a logical, generalized, single-target tracking problem. Therefore, it is of paramount importance to apply filters to meas More

Multi-target tracking is considered to be a significant issue in various areas of monitoring, supervision, and updated communication services. It is a logical, generalized, single-target tracking problem. Therefore, it is of paramount importance to apply filters to measure the direction or relative distance of the target from the viewer. Not showing the position of the sensor is the functional advantage of such sensors. One of the main issues in tracking is the dependence of estimation accuracy on the moving path of the viewer when the sensor only measures the direction of the target. With this background in mind, it is essential to estimate the position of the target. The present study aimed to determine the optimal path of the viewer in the tracking of two moving targets in order to improve the tracking performance. Target tracking was performed by a viewer only by measuring the direction of the target toward the viewer. Initially, the viewer path was introduced as a mathematical profile, and its coefficients were determined using an optimization algorithm, which demonstrated the lowest error rate in target tracking using the Kalman filter as an optimal estimator. Afterwards, another path was introduced, which was developed based on the estimates obtained by two Kalman filters, followed by the unscented Kalman filter. At the final stage, the most efficient method to continue the desired viewer path was proposed based on the comparison of the two methods, and the results of the optimization path were obtained using a multi-objective genetic algorithm. Manuscript profile

Open Access Article

11 - Design of Fault Tolerant System Using Model Predictive Control and Model-Based Fault Identification for a Chemical Reactor
Mehrdada Raeiisi Seyed Mohammad Kargar Dehnavi

Due to the possibility of fault in any industrial system's actuators, using a fault-tolerant control structure to compensate for the fault and maintain the system stability seems necessary. In this paper, the Continuously Stirred Tank Reactor model is evaluated, which h More

Due to the possibility of fault in any industrial system's actuators, using a fault-tolerant control structure to compensate for the fault and maintain the system stability seems necessary. In this paper, the Continuously Stirred Tank Reactor model is evaluated, which has a nonlinear model with temperature outputs and heating inlets of interconnected tanks. An Unscented Kalman filter is used to estimate the model's output dynamics, which has a suitable convergence speed and higher accuracy than other estimators. The nonlinear predictive control approach is used to apply the appropriate heating rate to the system to achieve the desired temperatures for each tank when there is no fault in the system. In the proposed design, to compensate for the fault, a sliding mode observer has been used to identify the fault. When a fault is detected, a fuzzy proportional derivative controller is used to control the system's fault. MATLAB software has been to evaluate the proposed method in different working modes of the reactor model. The simulation results show the good performance of the proposed method to compensate for the fault Manuscript profile

Open Access Article

12 - Sensorless Speed / Position Estimation for Permanent Magnet Synchronous Machine via Extended Kalman Filter
Meherdad Jafarboland Ehsan Babaei

Permanent Magnet Synchronous Machines (PMSM) are increasingly used because of their advantages over other machines, which include compactness, high efficiency, and well developed drives.. The substitution of the position sensors by advanced algorithms embedded in the co More

Permanent Magnet Synchronous Machines (PMSM) are increasingly used because of their advantages over other machines, which include compactness, high efficiency, and well developed drives.. The substitution of the position sensors by advanced algorithms embedded in the controls hardware and software has been investigated for the last couple of decades. This Paper presents the modeling, analysis, design and experimental validation of a robust sensor less control method for PMSM based on Extended Kalman Filter. The position/speed sensor less control scheme along with the power electronic circuitry is modeled. The performance of the proposed control is assessed and verified for different types of dynamic and static torque loads. Manuscript profile

Open Access Article

13 - Improvement of ECG Signal Noise Removal Using Recursive Kalman Filter
Sara Moein Zahra Beheshti

Nowadays, Kalman filter has been wildly used for solving the problem of real world. Kalman filter is a recursive filter that estimates the state of a linear dynamic system from a series of noisy measurements. One of the applications of Kalman filter is signal processing More

Nowadays, Kalman filter has been wildly used for solving the problem of real world. Kalman filter is a recursive filter that estimates the state of a linear dynamic system from a series of noisy measurements. One of the applications of Kalman filter is signal processing. In this paper, we use Kalman filter for electrocardiogram (ECG) signal noise removal. First accidental ECG signals are collected from Physiobank database and then Kalman filter is tuned for noise removing from ECG signals. In addition, we apply Finite Impulse Response (FIR) filter for ECG signal noise removing and finally we compare the performance of two filters using Mean Square Error (MSE) measurement. Results show the superior performance of Kalman filter for ECG signal noise removal.  Manuscript profile

Open Access Article

14 - Adaptive Control of the 3-Story Benchmark Building Equipped with MR Damper using Fractional Order Robust Controller
Ommegolsoum Jafarzadeh Seyed Arash Mousavi Ghasemi seyyed Mehdi Zahraei Ardashir Mohammadzadeh Ramin Vafaei Poursorkhabi

10.30495/civil.2023.702326

The goal of the present research is to propose a novel adaptive fractional order PID (AFOPID) controller whose parameters are tuned online by five exclusive multilayer perceptron (MLP) neural networks using the extended Kalman filter (EKF). An MLP neural network that is More

The goal of the present research is to propose a novel adaptive fractional order PID (AFOPID) controller whose parameters are tuned online by five exclusive multilayer perceptron (MLP) neural networks using the extended Kalman filter (EKF). An MLP neural network that is trained using the Back Propagation (BP) error algorithm is considered to identify the structural system and estimate the plant. The Jacobian of the model estimated online is utilized to apply to the controller. Considering the adaptive interval type-2 fuzzy neural networks (IT2FNN) and this issue that the compensator is tunned by EKF and feedback error learning strategy (FEL), the stability and robustness of this controller are increased against the estimation error, seismic disturbances, and some unknown nonlinear functions. In order to validate, the performance of the proposed controller is investigated on a 3-story nonlinear benchmark building equipped with semi-active dampers under far and near field earthquakes. In order to evaluate the effectiveness of the proposed controller equipped with a compensator in reducing seismic responses, the evaluation indices were discussed and compared with previous studies. The numerical results represent the substantial efficiency of the proposed adaptive controller (AFOPID) over the previous controllers such that J2 in the Hachinohe and Northridge earthquakes enhanced by up to 35% and more than 40%, respectively. In general, all indices ( J3  to J6 ) have experienced a considerable enhancement using the proposed method. Manuscript profile

Open Access Article

15 - بررسی ارتباط متقابل چرخه‌های مالی با کسب‌وکار در اقتصاد ایران
مصیب پهلوانی سید حسین میر جلیلی نفیسه کشتگر

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Open Access Article

16 - بررسی تغییرات کشش قیمتی تقاضای برق بخش خانگی در ایران با کاربرد روش فیلتر کالمن
علی اصغر اسماعیل نیا تیمور محمدی ابوطالب زمانی

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Open Access Article

17 - Smart portfolio using quantitative investment models
reza mansourian Nader Rezaei sayyedAli Nabavichashmi Ahmad Pouyanfar Ali Abdollahi

In the past few decades, the identification of state variables and parameters of a model from measured data has increased dramatically. This widespread growth has created a growing need for integrated models. Achieving sustained and long-term economic growth requires op More

In the past few decades, the identification of state variables and parameters of a model from measured data has increased dramatically. This widespread growth has created a growing need for integrated models. Achieving sustained and long-term economic growth requires optimal resource allocation, and this is not possible without the use of financial markets, especially efficient capital markets, so portfolio optimization and wealth allocation between different assets are among the most important issues in investing. In this research, in order to implement smart financial portfolio, it is tried to improve the existing optimization methods based on Sharp Ratio performance and to present an intelligent method for trading based on different algorithms. For this purpose, first, create a quantitative investment model using momentum algorithm and long-term investment model over a 6-year time horizon using monthly stock exchange data and then a set of smart models (general functions, general average and The general algorithm (developed by Kalman filter), which calculates the amount of capital using smart patterns to maximize return and avert negative return on equity investments and optimize capital investing to make the proposed structure perform better than other algorithms. Conventional and can fit and alternative approaches to achieve better results finally, the results indicate that the proposed model is effective and efficient. Manuscript profile

Open Access Article

18 - Dynamic survey of the relationship between gold and crude oil’s price uncertainty with banks stock index -method of state space
Reza Eyvazlu Saeed Bajalan Mostafa CHaharrahi

The study of dynamics and relations between markets has been one of the research subjects. This paper use state space in vector autoregressive moving average model (VARMA) to investigate the effect of gold and crude oil’s price uncertainty on stock returns of the More

The study of dynamics and relations between markets has been one of the research subjects. This paper use state space in vector autoregressive moving average model (VARMA) to investigate the effect of gold and crude oil’s price uncertainty on stock returns of the bank. In space-state equation system, the state variable is estimated by the Kalman filter and the specified parameters of the model by the maximum likelihood method. The results showed that gold and crude oil’s price uncertainty has a negative and significant effect on stock returns of the bank and the gold price uncertainty has a major effect on the stock returns of the bank. And furthermore, crude oil’s price uncertainty has a positive and significant effect on gold price uncertainty. In this research, daily OPEC crude oil prices, gold price (Bahar Azadi Coin- Old design) and banks stock index during the period 1390 to 1396-Shahrivar were used. Manuscript profile

Open Access Article

19 - مقایسه مدل‌ تلاطم تصادفی و مدل‌های GARCH، از طریق محاسبه ارزش
رسول سجاد شراره هدایتی شهره هدایتی

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Open Access Article

20 - بهره وری نیروی کار و بیکاری طبیعی در اقتصاد ایران؛ یک مطالعه بر پایه منحنی فیلیپس
رضا موسوی محسنی مزدا معطری جلیل خداپرست شیرازی نهال صفوی مقدم

    چکیده: این مقاله به دنبال یافتن ارتباط بین بهره وری نیروی کار و بیکاری طبیعی در اقتصاد ایران می باشد . در ابتدا به بررسی اجمالی فیلتر کالمن می پردازیم. این فیلتر به علت قابلیت حفظ ساختار اطلاعات مربوط به سری های زمانی، دامنه محدودیت نوسانا More

    چکیده: این مقاله به دنبال یافتن ارتباط بین بهره وری نیروی کار و بیکاری طبیعی در اقتصاد ایران می باشد . در ابتدا به بررسی اجمالی فیلتر کالمن می پردازیم. این فیلتر به علت قابلیت حفظ ساختار اطلاعات مربوط به سری های زمانی، دامنه محدودیت نوسانات (انحراف معیار) سری واقعی ، حول مقادیر روند بلندمدت آن و نیز امکان پیش بینی های آتی روند بلندمدت سری زمانی ، بسیار مفید می باشد . سپس از طریق به کارگیری این فیلتر نرخ بیکاری طبیعی و نرخ رشد بهره وری نیروی کار در اقتصاد ایران را محاسبه کرده و به بررسی رابطة بین این دو متغیر طی سال های 1338-1383 پرداخته شده است. نتایج به دست آمده حاکی از بالا بودن نگران کننده ی نرخ بیکاری طبیعی و همچنین پایین بودن نرخ بهره وری نیروی کار در اقتصاد ایران می باشد. نتیجه دیگری که گرفته می شود، وجود یک رابطه معکوس بین این دو متغیر در اقتصاد ایران است. به عبارت دیگر جهت کاهش بیکاری در اقتصاد ایران  باید بهبود بهره وری ، به عنوان اصلی ترین سیاست اقتصادی ، مدنظر قرار گیرد. جهت محاسبه توام ضرایب منحنی فیلیپس و بیکاری طبیعی به عنوان متغیر غیر قابل مشاهده ی ضمن تلفیق فیلتر کالمن به الگوریتم ژنتیک ، ساختار جدیدی برای محاسبات توأم مزبور ارائه شده است. Manuscript profile

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