• Title/Summary/Keyword: Estimation Methodology

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Conditional Density based Statistical Prediction

  • J Rama Devi;K. Koteswara Rao;M Venkateswara Rao
    • International Journal of Computer Science & Network Security
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    • v.23 no.6
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    • pp.127-139
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    • 2023
  • Numerous genuine issues, for example, financial exchange expectation, climate determining and so forth has inalienable arbitrariness related with them. Receiving a probabilistic system for forecast can oblige this dubious connection among past and future. Commonly the interest is in the contingent likelihood thickness of the arbitrary variable included. One methodology for expectation is with time arrangement and auto relapse models. In this work, liner expectation technique and approach for computation of forecast coefficient are given and likelihood of blunder for various assessors is determined. The current methods all need in some regard assessing a boundary of some accepted arrangement. In this way, an elective methodology is proposed. The elective methodology is to gauge the restrictive thickness of the irregular variable included. The methodology proposed in this theory includes assessing the (discretized) restrictive thickness utilizing a Markovian definition when two arbitrary factors are genuinely needy, knowing the estimation of one of them allows us to improve gauge of the estimation of the other one. The restrictive thickness is assessed as the proportion of the two dimensional joint thickness to the one-dimensional thickness of irregular variable at whatever point the later is positive. Markov models are utilized in the issues of settling on an arrangement of choices and issue that have an innate transience that comprises of an interaction that unfurls on schedule on schedule. In the nonstop time Markov chain models the time stretches between two successive changes may likewise be a ceaseless irregular variable. The Markovian methodology is especially basic and quick for practically all classes of classes of issues requiring the assessment of contingent densities.

Study of Peak Load Demand Estimation Methodology by Pearson Correlation Analysis with Macro-economic Indices and Power Generation Considering Power Supply Interruption

  • Song, Jiyoung;Lee, Jaegul;Kim, Taekyun;Yoon, Yongbeum
    • Journal of Electrical Engineering and Technology
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    • v.12 no.4
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    • pp.1427-1434
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    • 2017
  • Since the late 2000s, there has been growing preparation in South Korea for a sudden reunification of South and North Korea. Particularly in the power industry field, thorough preparations for the construction of a power infrastructure after reunification are necessary. The first step is to estimate the peak load demand. In this paper, we suggest a new peak demand estimation methodology by integrating existing correlation analysis methods between economic indicators and power generation quantities with a power supply interruption model in consideration of power consumption patterns. Through this, the potential peak demand and actual peak demand of the Nation, which experiences power supply interruption can be estimated. For case studies on North Korea after reunification, the potential peak demand in 2015 was estimated at 5,189 MW, while the actual peak demand within the same year was recorded as 2,461 MW. The estimated potential peak demand can be utilized as an important factor when planning the construction of power system facilities in preparation for reunification.

A Study on Vehicle Ego-motion Estimation by Optimizing a Vehicle Platform (차량 플랫폼에 최적화한 자차량 에고 모션 추정에 관한 연구)

  • Song, Moon-Hyung;Shin, Dong-Ho
    • Journal of Institute of Control, Robotics and Systems
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    • v.21 no.9
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    • pp.818-826
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    • 2015
  • This paper presents a novel methodology for estimating vehicle ego-motion, i.e. tri-axis linear velocities and angular velocities by using stereo vision sensor and 2G1Y sensor (longitudinal acceleration, lateral acceleration, and yaw rate). The estimated ego-motion information can be utilized to predict future ego-path and improve the accuracy of 3D coordinate of obstacle by compensating for disturbance from vehicle movement representatively for collision avoidance system. For the purpose of incorporating vehicle dynamic characteristics into ego-motion estimation, the state evolution model of Kalman filter has been augmented with lateral vehicle dynamics and the vanishing point estimation has been also taken into account because the optical flow radiates from a vanishing point which might be varied due to vehicle pitch motion. Experimental results based on real-world data have shown the effectiveness of the proposed methodology in view of accuracy.

Study on a New Response Function Estimation Method Using Neural Network (신경망 기법을 이용한 새로운 반응함수 추정 방법에 관한 연구)

  • Hoang, Thanh-Tra;Le, Tuan-Ho;Shin, Sangmun;Jeong, Woo-Sik;Kim, Chul-Soo
    • Journal of Korean Society for Quality Management
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    • v.41 no.2
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    • pp.249-260
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    • 2013
  • Purpose: The main objective of this paper is to propose an RD method by developing a neural network (NN)-based estimation approach in order to provide an alternative aspect of response surface methodology (RSM). Methods: A specific modeling procedure for integrating NN principles into response function estimations is identified in order to estimate functional relationships between input factors and output responses. Finally, a comparative study based on simulation is performed as verification purposes. Results: This simulation study demonstrates that the proposed NN-based RD method provides better optimal solutions than RSM. Conclusion: The proposed NN-based RD approach can be a potential alternative method to utilize many RD problems in competitive manufacturing nowadays.

Robot Posture Estimation Using Circular Image of Inner-Pipe (원형관로 영상을 이용한 관로주행 로봇의 자세 추정)

  • Yoon, Ji-Sup;Kang , E-Sok
    • The Transactions of the Korean Institute of Electrical Engineers D
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    • v.51 no.6
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    • pp.258-266
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    • 2002
  • This paper proposes the methodology of the image processing algorithm that estimates the pose of the inner-pipe crawling robot. The inner-pipe crawling robot is usually equipped with a lighting device and a camera on its head for monitoring and inspection purpose of defects on the pipe wall and/or the maintenance operation. The proposed methodology is using these devices without introducing the extra sensors and is based on the fact that the position and the intensity of the reflected light from the inner wall of the pipe vary with the robot posture and the camera. The proposed algorithm is divided into two parts, estimating the translation and rotation angle of the camera, followed by the actual pose estimation of the robot . Based on the fact that the vanishing point of the reflected light moves into the opposite direction from the camera rotation, the camera rotation angle can be estimated. And, based on the fact that the most bright parts of the reflected light moves into the same direction with the camera translation, the camera position most bright parts of the reflected light moves into the same direction with the camera translation, the camera position can be obtained. To investigate the performance of the algorithm, the algorithm is applied to a sewage maintenance robot.

Application of Fuzzy Information Representation Using Frequency Ratio and Non-parametric Density Estimation to Multi-source Spatial Data Fusion for Landslide Hazard Mapping

  • Park No-Wook;Chi Kwang-Hoon;Kwon Byung-Doo
    • Journal of the Korean earth science society
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    • v.26 no.2
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    • pp.114-128
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    • 2005
  • Fuzzy information representation of multi-source spatial data is applied to landslide hazard mapping. Information representation based on frequency ratio and non-parametric density estimation is used to construct fuzzy membership functions. Of particular interest is the representation of continuous data for preventing loss of information. The non-parametric density estimation method applied here is a Parzen window estimation that can directly use continuous data without any categorization procedure. The effect of the new continuous data representation method on the final integrated result is evaluated by a validation procedure. To illustrate the proposed scheme, a case study from Jangheung, Korea for landslide hazard mapping is presented. Analysis of the results indicates that the proposed methodology considerably improves prediction capabilities, as compared with the case in traditional continuous data representation.

A Study on Methodology of Soil Resistivity Estimation Using the BP (역전과 알고리즘(BP)을 이용한 대지저항률 추청 방법에 관한 연구)

  • Ryu, Bo-Hyeok;Wi, Won-Seok;Kim, Jeong-Hun
    • The Transactions of the Korean Institute of Electrical Engineers A
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    • v.51 no.2
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    • pp.76-82
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    • 2002
  • This paper presents the method of sail-resistivity estimation using the backpropagation(BP) neural network. Existing estimation programs are expensive, and their estimation methods need complex techniques and take much time. Also, those programs have not become well spreaded in Korea yet. Soil resistivity estimation method using BP algorithm has studied for the reason mentioned above. This paper suggests the method which differs from expensive program or graphic technology requiring many input stages, complicated calculation and professional knowledge. The equivalent earth resistivity can be presented immediately after inputting apparent resistivity through the personal computer with a simplified Program without many Processing stages. This program has the advantages of reasonable accuracy, rapid processing time and confident of anti users.

The Design of Fuzzy Controller by Means of Genetic Optimization and Estimation Algorithms

  • Oh, Sung-Kwun;Rho, Seok-Beom
    • KIEE International Transaction on Systems and Control
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    • v.12D no.1
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    • pp.17-26
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    • 2002
  • In this paper, a new design methodology of the fuzzy controller is presented. The performance of the fuzzy controller is sensitive to the variety of scaling factors. The design procedure is based on evolutionary computing (more specifically, a genetic algorithm) and estimation algorithm to adjust and estimate scaling factors respectively. The tuning of the soiling factors of the fuzzy controller is essential to the entire optimization process. And then we estimate scaling factors of the fuzzy controller by means of two types of estimation algorithms such as HCM (Hard C-Means) and Neuro-Fuzzy model[7]. The validity and effectiveness of the proposed estimation algorithm for the fuzzy controller are demonstrated by the inverted pendulum system.

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Regional Scale Rice Yield Estimation by Using a Time-series of RADARSAT ScanSAR Images

  • Li, Yan;Liao, Qifang;Liao, Shengdong;Chi, Guobin;Peng, Shaolin
    • Proceedings of the KSRS Conference
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    • 2003.11a
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    • pp.917-919
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    • 2003
  • This paper demonstrates that RADARSAT ScanSAR data can be an important data source of radar remote sensing for monitoring crop systems and estimation of rice yield for large areas in tropic and sub-tropical regions. Experiments were carried out to show the effectiveness of RADARSAT ScanSAR data for rice yield estimation in whole province of Guangdong, South China. A methodology was developed to deal with a series of issues in extracting rice information from the ScanSAR data, such as topographic influences, levels of agro-management, irregular distribution of paddy fields and different rice cropping systems. A model was provided for rice yield estimation based on the relationship between the backscatter coefficient of multi-temporal SAR data and the biomass of rice.

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