• Title/Summary/Keyword: Probabilistic modeling

Search Result 234, Processing Time 0.028 seconds

Spectrum Sensing Under Uncertain Channel Modeling

  • Biglieri, Ezio
    • Journal of Communications and Networks
    • /
    • v.14 no.3
    • /
    • pp.225-229
    • /
    • 2012
  • We examine spectrum sensing in a situation of uncertain channel model. In particular, we assume that, besides additive noise, the observed signal contains an interference term whose probability distribution is unknown, and only its range and maximum power are known. We discuss the evaluation of the detector performance and its design in this situation. Although this paper specifically deals with the design of spectrum sensors, its scope is wider, as the applicability of its results extends to a general class of problems that may arise in the design of receivers whenever there is uncertainty about how to model the environment in which one is expected to operate. The theory expounded here allows one to determine the performance of a receiver, by combining the available (objective) probabilistic information with (subjective) information describing the designer's attitude.

Resistive Hts-Fcl Emtdc Modeling By Using Probabilistic Design Methodology

  • Yoon, Jae-Young;Kim, Jong-Yul;Lee, Seung-Ryul
    • KIEE International Transactions on Power Engineering
    • /
    • v.4A no.2
    • /
    • pp.69-72
    • /
    • 2004
  • Nowadays, one of the serious problems in the KEPCO system is a much higher fault current than the SCC (Short Circuit Capacity) of the circuit breaker. Since superconductivity technology has become more developed, the HTS-FCL (High Temperature Superconductor-Fault Current Limiter) may become an attractive alternative to solving the fault current problem. In order to achieve the best performance, the parameters of HTS-FCL should be designed optimally. Under this setting, this paper presents the optimal design method of parameters for resistive type HTS-FCL using the Monte Carlo technique.

Online Learning Control for Network-induced Time Delay Systems using Reset Control and Probabilistic Prediction Method (네트워크 기반 시간지연 시스템을 위한 리세트 제어 및 확률론적 예측기법을 이용한 온라인 학습제어시스템)

  • Cho, Hyun-Cheol;Sim, Kwang-Yeul;Lee, Kwon-Soon
    • Journal of Institute of Control, Robotics and Systems
    • /
    • v.15 no.9
    • /
    • pp.929-938
    • /
    • 2009
  • This paper presents a novel control methodology for communication network based nonlinear systems with time delay nature. We construct a nominal nonlinear control law for representing a linear model and a reset control system which is aimed for corrective control strategy to compensate system error due to uncertain time delay through wireless communication network. Next, online neural control approach is proposed for overcoming nonstationary statistical nature in the network topology. Additionally, DBN (Dynamic Bayesian Network) technique is accomplished for modeling of its dynamics in terms of casuality, which is then utilized for estimating prediction of system output. We evaluate superiority and reliability of the proposed control approach through numerical simulation example in which a nonlinear inverted pendulum model is employed as a networked control system.

Fuzzy Project Scheduling of the R&D System under the Mechatronics Environment (메카트로닉스 환경하의 R&D System의 퍼지프로젝트 일정계획)

  • 이근희;이재성;주일권
    • Journal of Korean Society of Industrial and Systems Engineering
    • /
    • v.14 no.24
    • /
    • pp.169-177
    • /
    • 1991
  • The Existing Protect schedulings are mathematical nodes upon which probability control is based. In fact, under the mechatronics environment in the new product design and development, statistical information is very poor or sometimes non-existent. Probabilistic PERT/CPM methods are not always satisfying because those methods suppose that it is possible to apply central- limit theorem and there exists a critical path which is much mart critical than all the other paths. Fuzzy project scheduling is possibility based scheduling. For this reason, the Fuzzy Project Scheduling essential to design, development and control the new product under the mechatranics environment. This paper deals with a modeling on the project scheduling which use fuzzy set theory. Fuzzy concepts in the project scheduling are shown to be very useful and easy to work with in the R & D system.

  • PDF

Micro-Grids Reliability Enhancement Under Different Penetration Levels of Hybrid DG Units

  • Essam, M.;Atwa, Y.M.;El-Saadany, Ehab F.;Conti, Stefania;Rizzo, Santi Agatino
    • Journal of Electrical Engineering and Technology
    • /
    • v.13 no.4
    • /
    • pp.1407-1418
    • /
    • 2018
  • Novel mechanism of customized adequacy formulation is proposed in order to enhance micro grids system reliability. The mechanism accounts for 2-levles of load curtailment, and is mainly based on probabilistic load profile and hybrid Distributed Generation (DG) units modeling. The two load curtailments are needed in order to ensure adequate technical constraints at steady state condition during islanding mode of operation. The effectiveness of the proposed formulation has been verified using system independent analytical expressions for the evaluation of both reliability and Expected Energy Not Served (EENS) indices. The evaluation has examined the impact of different penetration levels of Hybrid DG Units in case study islands. Results show the enhancement of the overall distribution system reliability and the recommended conditions for successful islanding mode of operation.

Computational Challenges for Integrative Genomics

  • Kim, Junhyong;Magwene, Paul
    • Genomics & Informatics
    • /
    • v.2 no.1
    • /
    • pp.7-18
    • /
    • 2004
  • Integrated genomics refers to the use of large-scale, systematically collected data from various sources to address biological and biomedical problems. A critical ingredient to a successful research program in integrated genomics is the establishment of an effective computational infrastructure. In this review, we suggest that the computational infrastructure challenges include developing tools for heterogeneous data organization and access, innovating techniques for combining the results of different analyses, and establishing a theoretical framework for integrating biological and quantitative models. For each of the three areas - data integration, analyses integration, and model integration - we review some of the current progress and suggest new topics of research. We argue that the primary computational challenges lie in developing sound theoretical foundations for understanding the genome rather than simply the development of algorithms and programs.

Probabilistic Landslide Susceptibility Analysis and Verification using GIS and Remote Sensing Data at Penang, Malaysia

  • Lee, S.;Choi, J.;Talib, En. Jasmi Ab
    • Proceedings of the KSRS Conference
    • /
    • 2003.11a
    • /
    • pp.129-131
    • /
    • 2003
  • The aim of this study is to evaluate the hazard of landslides at Penang, Malaysia, using a Geographic Information System (GIS) and remote sensing. Landslide locations were identified in the study area from interpretation of aerial photographs and field surveys. The topographic and geologic data and satellite image were collected, processed and constructed into a spatial database using GIS and image processing. The used factors that influence landslide occurrence are topographic slope, topographic aspect topographic curv ature and distance from drainage from topographic database, geology and distance from lineament from the geologic database, land use from TM satellite image and vegetation index value from SPOT satellite image. Landslide hazardous area were analysed and mapped using the landslide-occurrence factors by probability - likelihood ratio - method. The results of the analysis were verified using the landslide location data. The validation results showed satisfactory agreement between the hazard map and the existing data on landslide location.

  • PDF

Probabilistic seismic demand of isolated straight concrete girder highway bridges using fragility functions

  • Bayat, Mahmoud;Ahmadi, Hamid Reza;Kia, Mehdi;Cao, Maosen
    • Advances in concrete construction
    • /
    • v.7 no.3
    • /
    • pp.183-189
    • /
    • 2019
  • In this study, it has been tried to prepare an analytical fragility curves for isolated straight continues highway bridges by considering different spectral intensity measures. A three-span concrete isolated bridge has been selected and the seismic performance of the bridge has been improved by Lead Rubber Bearing (LRB). Incremental Dynamic Analysis (IDA) is applied to the bridge in longitudinal direction. A suite of 14 earthquake ground motions from medium to sever motions are scaled and used for nonlinear time history analysis. Fragility function considers the relationship of earthquake intensity measures (IM) and probability of exceeding certain Damage State (DS). A full three dimensional finite element model of the isolated bridge has been developed and analyzed. A wide range of different intensity measures are selected and the optimal intensity measure which has the less dispersion is proposed.

A CASE STUDY ON INVESTMENT EVALUATION OF A PRIVATE SECTOR PROJECT WITH GEOTECHNICAL RISKS

  • Yoshiki Onoi;Hiroyasu Ohtsu
    • International conference on construction engineering and project management
    • /
    • 2005.10a
    • /
    • pp.824-829
    • /
    • 2005
  • This paper focuses on construction cost volatility for the purpose of private sector investment by use of a financial model with key indices of IRR and DSCR (Debt Service Coverage Ratio). A case project, 1,000 MW pumped storage hydropower plant, has shown that its financial impacts by cost volatility of underground works are less measured than interest rates impacts by interest rate of loans. Probabilistic analysis of costs under geotechnical conditions has been made by Indicator Kriging method. And, in the modeling of interest rates, geometric Brownian motion has been applied. Both of these impacts are measured on the same financial model.

  • PDF

Who knows what and to what extent - modeling the knowledge of the narrative agent

  • Hochang Kwon
    • Trans-
    • /
    • v.14
    • /
    • pp.65-92
    • /
    • 2023
  • The knowledge of the narrative agent not only constitutes the content and meaning of the narrative itself, but is also closely related to the emotional response of the recipient. Also, the disparity of knowledge between narrative agents is an important factor in making a narrative richer and more interesting. But It tends to be treated as a sub-topic of narration theory or genre/style studies rather than an independent subject of narrative studies or criticism. In this paper, I propose a model that can systematically and quantitatively analyze the knowledge of narrative agents. The proposed model consists of the knowledge structure that represents a narrative, the knowledge state that expresses the knowledge of narrative agent as a degree of belief, and the knowledge flow that means changes in the knowledge state according to the development of events. In addition, the formal notation of the knowledge structure and a probabilistic inference model that could obtain the state of knowledge were proposed, and the knowledge structure and knowledge flow were analyzed by applying the model to the actual narrative. It is expected that the proposed model will be of practical help in the creation and evaluation of narratives.