A query against incomplete or imprecise data in a database1, or a query whose search conditions are imprecise can both result in answers that do not satisfy the query completely. Such queries can be broadly termed as imprecise queries. Today’s database systems are designed largely for precise queries against a database of precise and complete data. Range queries (e.g., Age BETWEEN 20 AND 30) an...

agricultural sustainability refers to the ability of a farm to produce food indefinitely, without causing irreversible damage to ecosystem health. the main objective of this study was to formulate a structural model to analyze the effects of ecological, social, and economic factors on sustainable agricultural development in qazvin province of iran. to achieve this aim, a structural model with 4...

Traditional DEA models do not deal with imprecise data and assume that the data for all inputs and outputs are known exactly. Inverse DEA models can be used to estimate inputs for a DMU when some or all outputs and efficiency level of this DMU are increased or preserved. this paper studies the inverse DEA for fuzzy data. This paper proposes generalized inverse DEA in fuzzy data envelopment anal...

A manufacturing process cannot be released to production until it has been proven to be stable. Also, we cannot begin to talk about process capability until we have demonstrated stability in our process. This means that the process variation is the result of random causes only and all assignable or special causes have been removed. In complicated manufacturing processes, such as drilling proces...

Likelihood-based Imprecise Regression (LIR) is a recently introduced approach to regression with imprecise data. Here we consider a robust regression method derived from the general LIR approach and we establish an exact algorithm to determine the set-valued result of the LIR analysis in the special case of simple linear regression with interval data.

A new approach for ensemble construction based on restricting a set of weights of examples in training data to avoid overfitting is proposed in the paper. The algorithm called EPIBoost (Extreme Points Imprecise Boost) applies imprecise statistical models to restrict the set of weights. The updating of the weights within the restricted set is replaced by updating the weights in the linear combin...

Most algorithms in computational geometry tend to assume that all input is exact, with no imprecision or error. Most real-world data however, has some imprecision (for example due to measurement error). Thus, there exists a need for algorithms that can produce meaningful output for imprecise input data. In this thesis, I present results on the computation of upper and lower bounds on various ba...