Intelligent Computing for Vehicle Form Design: A Case Study of Sand Making Machine
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We develop inference for a two-sided matching model where the characteristics of agents on one side of the market are endogenous due to pre-matching investments. The model can be used to measure the impact of frictions in labour markets using a single cross-section of matched employer-employee data. The observed matching of workers to firms is the outcome of a discrete, two-sided matching process where firms with heterogeneous preferences over education sequentially choose workers according to an index correlated with worker preferences over firms. The distribution of education arises in equilibrium from a Bayesian game: workers, knowing the distribution of worker and firm types, invest in education prior to the matching process. Although the observed matching exhibits strong cross-sectional dependence due to the matching process, we propose an asymptotically valid inference procedure that combines discrete choice methods with simulation.
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Cahiers de Recherches Economiques du Département d'Econométrie et d'Economie politique (DEEP) (2014)
It is shown that a matching market with contracts may be embedded into a matching market with salaries under weaker assumptions on preferences than substitutability. In particular, the result applies to the recently studied problem of cadet-to-branch matching. As an application of the embedding result, a new class of mechanisms for matching markets with contracts is defined that generalize the firm-proposing deferred acceptance algorithm to the case where firms have unilaterally substitutable preferences.
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We develop inference for a two-sided matching model where the characteristics of agents on one side of the market are endogenous due to pre-matching investments. The model can be used to measure the impact of frictions in labour markets using a single cross-section of matched employer-employee data. The observed matching of workers to firms is the outcome of a discrete, two-sided matching process where firms with heterogeneous preferences over education sequentially choose workers according to an index correlated with worker preferences over firms. The distribution of education arises in equilibrium from a Bayesian game: workers, knowing the distribution of worker and firm types, invest in education prior to the matching process. Although the observed matching exhibits strong cross-sectional dependence due to the matching process, we propose an asymptotically valid inference procedure that combines discrete choice methods with simulation.
Discrete choice
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The prediction of hydrochemical types of salt lakes by probability artificial neural network model, which is one of the typical Radial basis function networks was studied. The good classing and predicting results were obtained. The average accuracy for predicting of hydrochemical types of salt lakes was 91.0%. Both the experimental results and structure analysis of neural networks indicated that the probability artificial neural network method is much better than the back-propagation (BP) neural network method . In fact, this study provides a new tool for chemical pattern recognition.
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Two dimensions to consider when deciding on a product design strategy are product design inputs and product design outputs. Product design inputs represent the number of markets that are consulted before an initial product is designed. Product design outputs represent the market(s) that the initial product(s) are actually designed for. The author examines the relationships between these dimensions and their impact on the product design strategy decision facing the global firm. Consideration is given to the forces driving a firm into a particular strategy and the tradeoffs involved in choosing a particular strategy.< >
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Taking motorcycle assembly enterprises for example,this paper analyzes the characteristics of assembly enterprises' matching job management,and its requirement of the balance between time and cost targets.Based on current supply chain modeling and analysis work,this paper gives a matching job model for assembly enterprises.According to its characteristics,this paper studies how to find critical paths having interval parameters and how to optimize the matching job based on time difference and critical paths.At last,the validity of the study result is proved with an implementation case.
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We introduce and study two-sided matching with incomplete information and interdependent valuations on one side of the market. An example of such a setting is a matching market between colleges and students in which colleges receive partially informative signals about students. Stability in such markets depends on the amount of information about matchings available to colleges. When colleges observe the entire matching, a stable matching mechanism does not generally exist. When colleges observe only their own matches, a stable mechanism exists if students have identical preferences over colleges, but may not exist if students have different preferences.
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The multiple variable synthetical predication problems with error back propagation training artificial neural network(BP neural network) is researched.To study the farmer income of Shanghuang experimental area is the background,BP's models of multiple variable synthetical predication were established.The results of experimental prediction show that the accuracy of predication by the neural network models is very high. They open up a new way to predict farmer income.
Backpropagation
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This paper investigates subject matching in the National University of Singapore (NUS). The matching process is conducted in a primary market and a secondary market. In the primary market, students and departments are matched by a centralized matching procedure, based on their submitted preferences. Students who are not satisfied with their allocations in the primary market can choose to join the secondary market. By comparing matching results in these two markets, we show how a centralized matching procedure and a decentralized matching procedure can work together to produce a desirable outcome, especially in a many-to-many matching market.
Optimal matching
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We develop inference for a two-sided matching model where the characteristics of agents on one side of the market are endogenous due to pre-matching investments. The model can be used to measure the impact of frictions in labour markets using a single cross-section of matched employer-employee data. The observed matching of workers to firms is the outcome of a discrete, two-sided matching process where firms with heterogeneous preferences over education sequentially choose workers according to an index correlated with worker preferences over firms. The distribution of education arises in equilibrium from a Bayesian game: workers, knowing the distribution of worker and firm types, invest in education prior to the matching process. Although the observed matching exhibits strong cross-sectional dependence due to the matching process, we propose an asymptotically valid inference procedure that combines discrete choice methods with simulation.
Discrete choice
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