When Is Data Processing Under Interval and Fuzzy Uncertainty Feasible: What if Few Inputs Interact? Does Feasibility Depend on How We Describe Interaction?

Kód výsledku v IS VaVaI

<a href="https://www.isvavai.cz/riv?ss=detail&h=RIV%2F00216208%3A11320%2F21%3A10437057" target="_blank" >RIV/00216208:11320/21:10437057 - isvavai.cz</a>

Výsledek na webu

<a href="https://doi.org/10.1007/978-3-030-47124-8_8" target="_blank" >https://doi.org/10.1007/978-3-030-47124-8_8</a>

DOI - Digital Object Identifier

<a href="http://dx.doi.org/10.1007/978-3-030-47124-8_8" target="_blank" >10.1007/978-3-030-47124-8_8</a>

Jazyk výsledku

angličtina

Název v původním jazyce

When Is Data Processing Under Interval and Fuzzy Uncertainty Feasible: What if Few Inputs Interact? Does Feasibility Depend on How We Describe Interaction?

Popis výsledku v původním jazyce

It is known that, in general, data processing under interval and fuzzy uncertainty is NP-hard-which means that, unless P = NP, no feasible algorithm is possible for computing the accuracy of the result of data processing. It is also known that the corresponding problem becomes feasible if the inputs do not interact with each other, i.e., if the data processing algorithm computes the sum of n functions, each depending on only one of the n inputs. In general, inputs and interact. If we take into account all possible interactions, and we use bilinear functions to describe this interaction, we get an NP-hard problem. This raises two natural questions: what if only a few inputs interact? What if the interaction is described by some other functions? In this paper, we show that the problem remains NP-hard if we use different formulas to describe the inputs&apos; interaction, and it becomes feasible if we only have interacting inputs-but remains NP-hard if the number of inputs is for any. (C) 2021, Springer Nature Switzerland AG.

Název v anglickém jazyce

When Is Data Processing Under Interval and Fuzzy Uncertainty Feasible: What if Few Inputs Interact? Does Feasibility Depend on How We Describe Interaction?

Popis výsledku anglicky

It is known that, in general, data processing under interval and fuzzy uncertainty is NP-hard-which means that, unless P = NP, no feasible algorithm is possible for computing the accuracy of the result of data processing. It is also known that the corresponding problem becomes feasible if the inputs do not interact with each other, i.e., if the data processing algorithm computes the sum of n functions, each depending on only one of the n inputs. In general, inputs and interact. If we take into account all possible interactions, and we use bilinear functions to describe this interaction, we get an NP-hard problem. This raises two natural questions: what if only a few inputs interact? What if the interaction is described by some other functions? In this paper, we show that the problem remains NP-hard if we use different formulas to describe the inputs&apos; interaction, and it becomes feasible if we only have interacting inputs-but remains NP-hard if the number of inputs is for any. (C) 2021, Springer Nature Switzerland AG.

Druh

C - Kapitola v odborné knize

CEP obor

—

OECD FORD obor

50201 - Economic Theory

Projekt

<a href="/cs/project/GA18-04735S" target="_blank" >GA18-04735S: Nové přístupy pro relaxační a aproximační techniky v deterministické globální optimalizaci</a><br>

Návaznosti

P - Projekt vyzkumu a vyvoje financovany z verejnych zdroju (s odkazem do CEP)

Rok uplatnění

2021

Kód důvěrnosti údajů

S - Úplné a pravdivé údaje o projektu nepodléhají ochraně podle zvláštních právních předpisů

Název knihy nebo sborníku

Studies in Fuzziness and Soft Computing

ISBN

978-3-030-47124-8

Počet stran výsledku

10

Strana od-do

91-100

Počet stran knihy

576

Název nakladatele

Springer

Místo vydání

Cham

Kód UT WoS kapitoly

—