• Title, Summary, Keyword: Probabilistic Choice Model

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Application of a Hybrid System of Probabilistic Neural Networks and Artificial Bee Colony Algorithm for Prediction of Brand Share in the Market

  • Shahrabi, Jamal;Khameneh, Sara Mottaghi
    • Industrial Engineering and Management Systems
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    • v.15 no.4
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    • pp.324-334
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    • 2016
  • Manufacturers and retailers are interested in how prices, promotions, discounts and other marketing variables can influence the sales and shares of the products that they produce or sell. Therefore, many models have been developed to predict the brand share. Since the customer choice models are usually used to predict the market share, here we use hybrid model of Probabilistic Neural Network and Artificial Bee colony Algorithm (PNN-ABC) that we have introduced to model consumer choice to predict brand share. The evaluation process is carried out using the same data set that we have used for modeling individual consumer choices in a retail coffee market. Then, to show good performance of this model we compare it with Artificial Neural Network with one hidden layer, Artificial Neural Network with two hidden layer, Artificial Neural Network trained with genetic algorithms (ANN-GA), and Probabilistic Neural Network. The evaluated results show that the offered model is outperforms better than other previous models, so it can be use as an effective tool for modeling consumer choice and predicting market share.

Estimation Model for Optimum Probabilistic Rainfall Intensity on Hydrological Area - With Special Reference to Chonnam, Buk and Kyoungnam, Buk Area - (수문지역별 최적확률강우강도추정모형의 재정립 -영.호남 지역을 중심으로 -)

  • 엄병헌;박종화;한국헌
    • Magazine of the Korean Society of Agricultural Engineers
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    • v.38 no.2
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    • pp.108-122
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    • 1996
  • This study was to introduced estimation model for optimum probabilistic rainfall intensity on hydrological area. Originally, probabilistic rainfall intensity formula have been characterized different coefficient of formula and model following watersheds. But recently in korea rainfall intensity formula does not use unionize applyment standard between administration and district. And mingle use planning formula with not assumption model. Following the number of year hydrological duration adjust areal index. But, with adjusting formula applyment was without systematic conduct. This study perceive the point as following : 1) Use method of excess probability of Iwai to calculate survey rainfall intensity value. 2) And, use method of least squares to calculate areal coefficient for a unit of 157 rain gauge station. And, use areal coefficient was introduced new probabilistic rainfall intensity formula for each rain gauge station. 3) And, use new probabilistic rainfall intensity formula to adjust a unit of fourteen duration-a unit of fifteen year probabilistic rainfall intensity. 4) The above survey value compared with adjustment value. And use three theory of error(absolute mean error, squares mean error, relative error ratio) to choice optimum probabilistic rainfall intensity formula for a unit of 157 rain gauge station.

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Probabilistic Distribution and Variability of Geotechnical Properties with Randomness Characteristic (무작위성을 보이는 지반정수의 확률분포 및 변동성)

  • Kim, Dong-Hee;Lee, Ju-Hyoung;Lee, Woo-Jin
    • Journal of the Korean Geotechnical Society
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    • v.25 no.11
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    • pp.87-103
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    • 2009
  • To determine the reliable probabilistic distribution model of geotechnical properties, outlier and randomness test for analysis data, parameter estimation of probabilistic distribution model, and goodness-of-fit test for model parameter and probabilistic distribution model have to be performed in sequence. In this paper, the probabilistic distribution model's geotechnical properties of Songdo area in Incheon are estimated by the above proposed procedure. Also, the coefficient of variation (COV) representing the variability of geotechnical properties is determined for several geotechnical properties. Reliable probabilistic distribution model and COV of geotechnical properties can be used for probability-based design procedure and reasonable choice of design value in deterministic design method.

Probabilistic penalized principal component analysis

  • Park, Chongsun;Wang, Morgan C.;Mo, Eun Bi
    • Communications for Statistical Applications and Methods
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    • v.24 no.2
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    • pp.143-154
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    • 2017
  • A variable selection method based on probabilistic principal component analysis (PCA) using penalized likelihood method is proposed. The proposed method is a two-step variable reduction method. The first step is based on the probabilistic principal component idea to identify principle components. The penalty function is used to identify important variables in each component. We then build a model on the original data space instead of building on the rotated data space through latent variables (principal components) because the proposed method achieves the goal of dimension reduction through identifying important observed variables. Consequently, the proposed method is of more practical use. The proposed estimators perform as the oracle procedure and are root-n consistent with a proper choice of regularization parameters. The proposed method can be successfully applied to high-dimensional PCA problems with a relatively large portion of irrelevant variables included in the data set. It is straightforward to extend our likelihood method in handling problems with missing observations using EM algorithms. Further, it could be effectively applied in cases where some data vectors exhibit one or more missing values at random.

Probabilistic Location Choice and Markovian Industrial Migration a Micro-Macro Composition Approach

  • Jeong, Jin-Ho
    • Journal of the Korean Regional Science Association
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    • v.11 no.1
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    • pp.31-60
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    • 1995
  • The distribution of economic activity over a mutually exclusive and exhaustive categorical industry-region matrix is modeled as a composition of two random components: the probability-like share distribution of jobs and the dynamic evolution of absolute aggregates. The former describes the individual activity location choice by comparing the predicted profitability of the current industry-region pair against that of all other alternatives based on the available information on industry-specific, region specific, or activity specific attributes. The latter describes the time evolution of macro-level aggregates using a dynamic reduced from model. With the seperation of micro choice behavior and macro dynamic aggregate constraint, the usual independence and identicality assumptions become consistent with the activity share distribution, hence multi-regional industrial migration can be represented by a set of probability evolution equations in a conservative Markovian from. We call this a Micro-Macro Composition Approach since the product of the aggregate prediction and the predicted activity share distribution gives the predicted activity distribution gives the predicted activity distribution which explicitly considers the underlying individual choice behavior. The model can be applied to interesting practical problems such as the plant location choice of multinational enterprise, the government industrial ploicy to attract international firms, and the optimal tax-transfer mix to influence activity location choice. We consider the latter as an example.

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Estimation of Optimal Modal Split Considering the Subsidy Policy - In the Case of Dual Mode Trailer (보조금 정책을 고려한 적정 수송 분담률 추정 모형 - Dual Mode Trailer(DMT) 사례를 중심으로)

  • Park, Bum-Hwan;Kim, Chung-Soo;Lee, Kang-Won
    • Journal of the Korean Society for Railway
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    • v.12 no.2
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    • pp.205-211
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    • 2009
  • There is need to reform the road-based logistic transportation system into the railway-based logistics transportation system in order to decrease the total social cost related with logistics transportation. And new transportation modes such as dual mode trailer (DMT) are under consideration, which are expected to decrease current market share of road. But, most of current studies about estimating economical efficiency are focused on developing the probabilistic choice model and then estimating the market share of each mode. We present an approach to compute the optimal market share of each mode in terms of total social cost. To do so, we suggest an optimization model capturing both user choice to maximize his utility and subsidy policy intended to minimize total social cost, simultaneously. Using this model, we present the optimal modal split of container freight.

A Study ort the Facilities Distribution based on the Choice Model of the Outdoor Leisure-Facilities in a Neighbourhood Unit of the Megalopolis Citizens. - in terms of the distribution of Outdoer Leisure-Facilities - (대도시 주민의 근린 실외여가시설 선택모형을 기초로 한 시설지 배분에 관한 연구)

  • 최기수;김한배;진양교;진상철;김석기
    • Journal of the Korean Institute of Landscape Architecture
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    • v.23 no.1
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    • pp.141-156
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    • 1995
  • This research is executed to find out the boundary of use by the conscious of local residents and to get the basic materials for the distribution of outdoor leisure-facilities. The map of use distribution of the outdoor leisure-facilities in a neighbourhood unit is made by applying a concept of the probabilistic contour line based on the choice model of outdoer leisure-facilities in the city of Seoul, Taegu an\ulcorner Kwangju. The results are listed as follows. 1) The use of outdoor leisure-facilities is influenced on the accessibility by the physical obstacles of streets and hills, etc. 2) The limitation of uses applying the model of choice probability are different according to the accessibility, the percentage of utilities and the arriving range based on the questionnaires which are surveyed the choice of outdoor leisure facilities of the residents of Seoul, Taegu and Kwangju. 3) The distribution of outdoor leisure facilities is decided by the limitation of use with the conscious of local residents.

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Probabilistic assessment on the basis of interval data

  • Thacker, Ben H.;Huyse, Luc J.
    • Structural Engineering and Mechanics
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    • v.25 no.3
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    • pp.331-345
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    • 2007
  • Uncertainties enter a complex analysis from a variety of sources: variability, lack of data, human errors, model simplification and lack of understanding of the underlying physics. However, for many important engineering applications insufficient data are available to justify the choice of a particular probability density function (PDF). Sometimes the only data available are in the form of interval estimates which represent, often conflicting, expert opinion. In this paper we demonstrate that Bayesian estimation techniques can successfully be used in applications where only vague interval measurements are available. The proposed approach is intended to fit within a probabilistic framework, which is established and widely accepted. To circumvent the problem of selecting a specific PDF when only little or vague data are available, a hierarchical model of a continuous family of PDF's is used. The classical Bayesian estimation methods are expanded to make use of imprecise interval data. Each of the expert opinions (interval data) are interpreted as random interval samples of a parent PDF. Consequently, a partial conflict between experts is automatically accounted for through the likelihood function.

A Study on the Development of an Estimation Model: The Psychological Cost of Traffic Accidents (교통사고의 심리적 비용 산정모형 개발에 관한 연구)

  • Yu, Jeong-Bok;Shon, Eui-Young
    • Journal of Korean Society of Transportation
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    • v.26 no.3
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    • pp.211-221
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    • 2008
  • This dissertation studied the psychological cost, which converted the mental pain suffered by the victim of a traffic accident and his/her family, friends and people around him/her into social costs. Three methodologies - Choice Experiments, Direct Question and Dichotomous Choice Question - were used to design questionnaires, and models were built for each questionnaire design method. When building models, a logit model was used, which is used most frequently in probabilistic choice model. And the tobitmodel was used to make direct questionnaires. When verifying these models, although there were some differences in each model, suitability of most models and credibility of each coefficient were meaningful around the credibility level of 95%. According to the analysis, domestic psychological cost produced through the assessment model of psychological cost was 15.63 million won per person or 5.1 trillion in total, assuming 37.1% of total traffic accident cost.

Probabilistic Models for Local Patterns Analysis

  • Salim, Khiat;Hafida, Belbachir;Ahmed, Rahal Sid
    • Journal of Information Processing Systems
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    • v.10 no.1
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    • pp.145-161
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    • 2014
  • Recently, many large organizations have multiple data sources (MDS') distributed over different branches of an interstate company. Local patterns analysis has become an effective strategy for MDS mining in national and international organizations. It consists of mining different datasets in order to obtain frequent patterns, which are forwarded to a centralized place for global pattern analysis. Various synthesizing models [2,3,4,5,6,7,8,26] have been proposed to build global patterns from the forwarded patterns. It is desired that the synthesized rules from such forwarded patterns must closely match with the mono-mining results (i.e., the results that would be obtained if all of the databases are put together and mining has been done). When the pattern is present in the site, but fails to satisfy the minimum support threshold value, it is not allowed to take part in the pattern synthesizing process. Therefore, this process can lose some interesting patterns, which can help the decider to make the right decision. In such situations we propose the application of a probabilistic model in the synthesizing process. An adequate choice for a probabilistic model can improve the quality of patterns that have been discovered. In this paper, we perform a comprehensive study on various probabilistic models that can be applied in the synthesizing process and we choose and improve one of them that works to ameliorate the synthesizing results. Finally, some experiments are presented in public database in order to improve the efficiency of our proposed synthesizing method.