Abstract: We introduce the power average to provide an aggregation operator which allows argument values to support each other in the aggregation process. The properties of this operator are described. We discuss the idea of a power median. We introduce some possible formulations for the support function used in the power average.
Aggregation Operators and Commuting IRIT. Aggregation Operators and Commuting Susanne Saminger, Radko Mesiar, and Didier Dubois Abstract—Commuting is an important property in any two-step information merging procedure where the results should not depend on the order in which the single steps are preformed.
aggregation operator that uni es the,those functions that use probabilistic information in the aggregation process Some exam-ples are the aggregation with . Chat Online; TERMINOLOGY ON STATISTICAL METADATA. 2 _____ Terminology on Statistical Metadata aggregation process operator Definition: A mathematical operator used for specification of .
Aggregation in MongoDB is an operation used to process the data that returns the computed results. Aggregation basically groups the data from multiple documents and operates in many ways on those
Aggregation is the process of consolidating multiple values into a single value. For example, data can be collected on a daily basis and aggregated into a value for the week, the weekly data can be aggregated into a value for the month, and so on.
The forecasting model involving the distribution of electric power load is investigated in . Different aggregation of OWA operators is presented in . The methods of data smooth- ing are
Definition. Formally an OWA operator of dimension is a mapping : → that has an associated collection of weights = [, ,] lying in the unit interval and summing to one and with (, ,) = ∑ =where is the j th largest of the .. By choosing different W one can implement different aggregation operators. The OWA operator is a non-linear operator as a result of the process of determining the b j.
In addition, pipeline stages can use operators for tasks such as calculating the average or concatenating a string. The pipeline provides efficient data aggregation using native operations within MongoDB, and is the preferred method for data aggregation in MongoDB. The aggregation pipeline can operate on a sharded collection.
2018-10-17· Many properties of these operators are investigated. Then, we developed a model for multiple attribute decision-making problem for bipolar fuzzy Dombi aggregation operators under the bipolar fuzzy environment. Finally, a practical example for selection of investment alternatives is given to demonstrate for the utility and application of the
This article presents a new aggregation system applied to fuzzy decision making. The fuzzy generalized unified aggregation operator (FGUAO) is a system that integrates many operators by adding a new aggregation process that considers the relevance that each operator has in the analysis.
and (AO3) are referred to as n-ary aggregation operators. Depending on the requirements applied to the aggregation process several properties for aggregation operators have been introduced. We only mention those few which are relevant for our further investigations. For more elaborated details on aggregation operators we refer to, e.g., .
Imitating an SQL aggregation query using the Aggregate operator. This Example Process discusses an arbitrary scenario. Then describes how this scenario could be handled using SQL aggregation functions. Then the SQL's solution is imitated in Miner. The Aggregate operator plays a key role in this process.
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In this paper, based on score function and accuracy function, we introduce a method for the comparison between two intuitionistic fuzzy values and then develop some aggregation operators, such as
The input to an aggregation process is the documents in collections and the results is also a document or a number of documents. Aggregation stages involve operators such as addition, averaging values for given fields, finding the maximum and minimum values among many more operators. This makes the analysis of data even more simplified.
prioritized average operator and the linguistic aggregation operator . 2.1 Basic operators 2.1.1 OWA operators using IFSs to solve MADM in Arithmetic mean operator In real life decision situation, the aggregation problems in the MCDM are solved using the scoring techniques such as the weighted aggregation operator based on
aggregation process operator Definition: A mathematical operator used for specification of aggregation processes with statistical data broader: aggregation process related: aggregation process argument narrower: aggregation process argument Definition: A variable used as a subscript to reference a set of statistical data that
An aggregation processing system includes a data transmission unit for transforming data which is a target of an aggregation process into a format of a tuple having a key and for transmitting the tuple to a data processing unit, and the data processing unit for performing an aggregation process of a tuple which has been transmitted. When a tuple transmitted from the data transmission unit is
The following illustration shows the results of two different aggregation operations on a sequence of numbers. The first operation sums the numbers. The second operation returns the maximum value in the sequence. The standard query operator methods that perform aggregation operations are listed in the following section. Methods
Apart from this, another important mathematical operation is logarithm operational laws (LOL), which are very useful in the field of the aggregation process. In this manner, with the developing sound of the PFS both inside and out and scope, there is a need to build up some new operational laws and aggregation operators. By keeping the benefits
Aggregation only occurs once for each output variable, which is before the final defuzzification step. The input of the aggregation process is the list of truncated output functions returned by the implication process for each rule. The output of the aggregation process is one fuzzy set for each output variable.
As an effective aggregation tool, power average (PA) allows the input arguments being aggregated to support and reinforce each other, which provides more versatility in the information aggregation process. Under the probabilistic linguistic term environment, we deeply investigate the new power aggregation (PA) operators for fusing the probabilistic linguistic term sets (PLTSs).
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