## Complex Uncertain(복잡한 불확실성)란 무엇입니까?

Complex Uncertain 복잡한 불확실성 - Results show that the developed model could provide the decision-makers with not only the best or the optimum range of system net benefits but also the probability of obtaining a given benefit under complex uncertainties.^{[1]}Situation awareness (SA) has been recognized as a critical guarantee for the stable and secure operation of electric power systems, especially under complex uncertainties after renewable energy integration.

^{[2]}However, evaluating operational programs by quantifying seeding impacts remains a challenging task subject to complex uncertainties.

^{[3]}In this paper, a new fuzzy credibility-based double-sided chance-constrained programming (FCDCP) model is proposed for the capacitated MPS/MRP integrated programming problem under complex uncertainty.

^{[4]}It was also shown which components of complex uncertainty can be omitted from the analysis without losing the accuracy of its estimation.

^{[5]}The derivation of the robust counterpart formulation using the duality theory is nontrivial, especially for complex uncertainty sets.

^{[6]}In this context, we address two crucial consequences for planning the electricity transition: (a) substantially more complex uncertainties in variable renewable energy and (b) a requirement to co-ordinate extensive transmission investment with the newly located generating facilities.

^{[7]}In addition, gray relational analysis (GRA) was used to analyze the complex uncertainty affecting the results.

^{[8]}For the unmeasurable and boundary-unknown uncertainties, the adaptive fuzzy logic scheme is employed to approximate the complex uncertainties.

^{[9]}In order to consider the complex uncertainty in actual power system, according to the line protection actions, environmental and weather factors and human errors caused by the line fault and line overload to get the line outage probability, further set up cascading failure risk assessment model of power grid considering line outage rate.

^{[10]}Aiming at the high-dimensional, multi- variable, non-linear and complex uncertainty problem of power grid project cost control index prediction, this paper proposes a power grid project cost control index prediction method based on variational Bayesian deep learning theory.

^{[11]}It is of vital importance to formulate optimal management strategies for decision-makers by considering conflicting objectives among system cost and environmental risk under complex uncertainties.

^{[12]}Besides, the control of the tank vehicle running system and tank gun bidirectional stabilization system are unified to deal with the control signal delay caused by complex uncertainties on the battlefield.

^{[13]}The fire front representation is based on the complex uncertainty model that allows us to smooth the effects of distortions, interferences, and noises.

^{[14]}This article takes the complex uncertainty in the carrying process of water resources system as the research object.

^{[15]}Communication about the "unknowable unknown" occurs infrequently and ineffectively, and there is little research on improving communication in the face of epistemic and complex uncertainty.

^{[16]}It provides all the possible probability features for Smart Factory with complex uncertainty.

^{[17]}Unfortunately, they are subject to a complex uncertainty structure due to complicated proxy–climate relations and sparse data, which makes interpolation between samples difficult.

^{[18]}With the increasing integration of wind power and demand response into power system, the complex uncertainties from supply-side and demand-side have brought great challenges to daily operation of the power system.

^{[19]}Due to the complex uncertainty of working loads and design parameters, time-dependent reliability estimation is time-consuming.

^{[20]}In this study, a type-2 fuzzy chance-constrained fractional integrated programming (T2FCFP) approach is developed for the planning of sustainable management in an electric power system (EPS) under complex uncertainties.

^{[21]}The study is concerned with the representation and aggregation of complex uncertainty information.

^{[22]}However, non-probabilistic methods, such as evidence theory [7], grey system theory [33], probability-box [27], and fuzzy theory [15, 30], have been proposed and developed for reliability analysis of complex uncertainty MSS.

^{[23]}While existing production planning has numerous uncertainties and nonlinear characteristics, the circular economy-based production planning constitutes more complex uncertainties and nonlinear characteristics that result from an uncertain return rate, demand uncertainties, and nonlinear return on investment costs.

^{[24]}By comparison, the proposed methodology can not only clarify the physical meaning of penalty but deal with more complex uncertainty than previous methods.

^{[25]}In this paper, suffering from both complex uncertainties and underactuations, accurate trajectory tracking control problem of an asymmetric underactuated surface vehicle (AUSV) is first addressed by guiding yaw dynamics which are free of persistent excitation (PE).

^{[26]}This paper aims at developing a novel preference ranking organization method for enrichment evaluations (PROMETHEE) using a Pythagorean fuzzy combinative distance-based precedence approach under complex uncertainty based on Pythagorean fuzzy sets.

^{[27]}For the identification and modelling problems of a nonlinear system with complex uncertainties, a self-organising interval type-2 fuzzy neural network structure with asymmetric membership functions (SIT2FNN-AMF) is developed.

^{[28]}The aim of this article is to develop a novel multiple criteria decision analysis (MCDA) method using a Pearson‐like correlation‐based Pythagorean fuzzy (PF) compromise approach under complex uncertainty based on PF sets and interval‐valued Pythagorean fuzzy (IVPF) sets.

^{[29]}More than this, power demand and other factors are also facing many complex uncertainties.

^{[30]}Keep this feature in mind, the main purpose of this paper is to investigate a weighted induced aggregation approach for decisionmaking problem concerning fi nancing selection with complex uncertainty in term of intuitionistic linguistic (IL) information.

^{[31]}

nan

^{[1]}nan

^{[2]}nan

^{[3]}nan

^{[4]}nan

^{[5]}nan

^{[6]}nan

^{[7]}nan

^{[8]}nan

^{[9]}nan

^{[10]}nan

^{[11]}nan

^{[12]}nan

^{[13]}nan

^{[14]}nan

^{[15]}nan

^{[16]}복잡한 불확실성이 있는 Smart Factory에 가능한 모든 확률 기능을 제공합니다.

^{[17]}불행히도, 그것들은 복잡한 프록시-기후 관계와 희소 데이터로 인해 복잡한 불확실성 구조에 종속되어 샘플 간의 보간을 어렵게 만듭니다.

^{[18]}풍력 및 수요 대응이 전력 시스템에 통합되는 경우가 증가함에 따라 공급 측면과 수요 측면의 복잡한 불확실성으로 인해 전력 시스템의 일상적인 운영에 큰 어려움이 발생했습니다.

^{[19]}작업 부하 및 설계 매개변수의 복잡한 불확실성으로 인해 시간 종속적 신뢰도 추정에는 시간이 많이 걸립니다.

^{[20]}이 연구에서는 복잡한 불확실성 하에서 전력 시스템(EPS)의 지속 가능한 관리를 계획하기 위해 유형 2 퍼지 기회 제한 분수 통합 프로그래밍(T2FCFP) 접근 방식을 개발했습니다.

^{[21]}이 연구는 복잡한 불확실성 정보의 표현 및 집계에 관한 것입니다.

^{[22]}그러나 복소불확도 MSS의 신뢰도 분석을 위해 증거이론[7], 회색시스템이론[33], 확률박스[27], 퍼지이론[15, 30]과 같은 비확률적 방법이 제안되고 발전되어 왔다. .

^{[23]}기존의 생산계획은 많은 불확실성과 비선형적인 특성을 가지고 있는 반면, 순환경제 기반의 생산계획은 불확실한 수익률, 수요의 불확실성, 투자비용에 대한 비선형적인 수익률로 인해 보다 복잡한 불확실성과 비선형적인 특성을 구성한다.

^{[24]}이에 비해 제안된 방법론은 벌칙의 물리적 의미를 명확히 할 수 있을 뿐만 아니라 기존 방법보다 더 복잡한 불확실성을 다룰 수 있다.

^{[25]}이 논문에서는 복잡한 불확실성과 과소작동을 모두 겪고 있는 비대칭 과소작동 표면 차량(AUSV)의 정확한 궤적 추적 제어 문제를 먼저 지속적 여기(PE)가 없는 안내 요 역학을 통해 해결합니다.

^{[26]}이 논문은 Pythagorean 퍼지 집합을 기반으로 하는 복잡한 불확실성에서 Pythagorean 퍼지 조합 거리 기반 우선 순위 접근 방식을 사용하여 농축 평가를 위한 새로운 선호 순위 구성 방법(PROMETHEE)을 개발하는 것을 목표로 합니다.

^{[27]}복잡한 불확도를 가진 비선형 시스템의 식별 및 모델링 문제를 위해 비대칭 멤버십 함수(SIT2FNN-AMF)가 있는 자가 구성 간격 유형 2 퍼지 신경망 구조가 개발되었습니다.

^{[28]}이 기사의 목적은 PF 세트 및 간격 값 피타고라스 퍼지(IVPF) 세트를 기반으로 한 복잡한 불확실성에서 Pearson-like 상관 관계 기반 Pythagorean 퍼지(PF) 절충 접근법을 사용하여 새로운 다중 기준 결정 분석(MCDA) 방법을 개발하는 것입니다. .

^{[29]}이 외에도 전력 수요 및 기타 요인들도 많은 복잡한 불확실성에 직면해 있습니다.

^{[30]}이 기능을 염두에 두십시오. 이 문서의 주요 목적은 직관적 언어(IL) 정보 측면에서 복잡한 불확실성을 가진 재정 선택과 관련된 의사 결정 문제에 대한 가중 유도 집계 접근 방식을 조사하는 것입니다.

^{[31]}

## Model Complex Uncertain

This paper discusses the construction of a type-2 fuzzy B-spline model to model complex uncertainty of surface data.^{[1]}Several approaches such as physical models, conceptual models and statistical/black-box models are used to model complex uncertain peak flows in rivers.

^{[2]}

nan

^{[1]}물리적 모델, 개념적 모델 및 통계적/블랙박스 모델과 같은 여러 접근 방식은 강의 복잡하고 불확실한 피크 흐름을 모델링하는 데 사용됩니다.

^{[2]}

## Represent Complex Uncertain

Numerous research papers and several engineering applications have proved that the fuzzy set theory is an intelligent effective tool to represent complex uncertain information.^{[1]}In this paper, we aim to develop a consistent framework of formulating demand uncertainties in single-period (newsvendor) problems, where a set of discrete assessment grades and/or grade intervals are used to represent complex uncertainties in both quantitative and qualitative evaluations.

^{[2]}

nan

^{[1]}이 백서에서 우리는 단일 기간(뉴스 벤더) 문제에서 수요 불확실성을 공식화하는 일관된 프레임워크를 개발하는 것을 목표로 합니다. 여기서 일련의 개별 평가 등급 및/또는 등급 간격을 사용하여 양적 및 정성적 평가 모두에서 복잡한 불확실성을 나타냅니다.

^{[2]}

## complex uncertain information 복잡한 불확실한 정보

Research regarding MCGDM is quite challenging due to both the structure of the problem and the existence of complex uncertain information.^{[1]}Numerous research papers and several engineering applications have proved that the fuzzy set theory is an intelligent effective tool to represent complex uncertain information.

^{[2]}Owing to the limitations of Pythagorean fuzzy and intuitionistic fuzzy sets, scientists have developed a distinct and successive fuzzy set called the q-rung orthopair fuzzy set (q-ROFS), which eliminates restrictions encountered by decision-makers in multicriteria decision making (MCDM) methods and facilitates the representation of complex uncertain information in real-world circumstances.

^{[3]}The purpose of this manuscript is to propose a new concept called complex q-rung orthopair linguistic sets (Cq-ROLSs) to cope with complex uncertain information in real decision-making problems.

^{[4]}The probability multi-valued neutrosophic sets (PMVNSs) have the power to describe complex uncertain information more comprehensively.

^{[5]}

nan

^{[1]}nan

^{[2]}nan

^{[3]}이 원고의 목적은 실제 의사 결정 문제에서 복잡하고 불확실한 정보에 대처하기 위해 복잡한 q-렁 직교 쌍 언어 집합(Cq-ROLS)이라는 새로운 개념을 제안하는 것입니다.

^{[4]}확률 다중값 호중성 집합(PMVNS)은 복잡하고 불확실한 정보를 보다 포괄적으로 설명할 수 있는 능력이 있습니다.

^{[5]}

## complex uncertain sequence 복잡한 불확실한 시퀀스

The aim of this treatise is to introduce the concept of strongly almost convergence in complex uncertain sequences.^{[1]}The aim of this paper is to introduce the complex uncertain sequence space [Formula: see text] related to the [Formula: see text] space.

^{[2]}In this paper, we intend to make a new approach to introduce the concept of tn-statistical convergence of complex uncertain sequences like tn-statistical convergence almost surely (a.

^{[3]}In this paper, as a part of uncertain theory, we discuss various concepts of convergence and statistical convergence of complex uncertain sequences.

^{[4]}

## complex uncertain multus 복잡한 불확실 로트

Thus, this selection process can be considered as a complex uncertain multi-criteria decision making (MCDM) problem.^{[1]}Generally, EVCS location selection is treated as complex uncertain multi-criteria decision making (MCDM) problem because of the existence of many quantitative and qualitative influencing factors.

^{[2]}It can be used as a new reliability analysis method for the complex uncertain multi-state systems.

^{[3]}

nan

^{[1]}nan

^{[2]}복잡하고 불확실한 다중 상태 시스템에 대한 새로운 신뢰성 분석 방법으로 사용할 수 있습니다.

^{[3]}

## complex uncertain variable 복잡한 불확실 변수

In this paper, we introduce the notion of lacunary convergence for double sequences of complex uncertain variables.^{[1]}In this treatise, we extend the study of almost convergence by introducing double sequences of complex uncertain variable.

^{[2]}In this paper, we have developed the idea of Riesz mean, Riesz convergent in measure and Riesz convergent almost surely in complex uncertain variables.

^{[3]}

## complex uncertain system

In this paper, we propose the concept of mean multi-objective cost of uncertainty (multi-objective MOCU) that can be used for objective-based quantification of uncertainty for complex uncertain systems considering multiple operational objectives.^{[1]}A deregulated power system is considered to be a highly complex uncertain system due to the presence of multiple bilateral transactions.

^{[2]}

nan

^{[1]}규제 완화된 전력 시스템은 다중 양자 거래가 존재하기 때문에 매우 복잡한 불확실한 시스템으로 간주됩니다.

^{[2]}

## complex uncertain nonlinear

In this paper, an observer-based decentralized event-triggered neuro-adaptive controller (DETNAC) is presented for complex uncertain nonlinear systems.^{[1]}For the more complex uncertain nonlinear functions in the system, in this paper, a single hidden layer neural network was used for compensation and the fault-tolerant control was realized by combining the dynamic gain.

^{[2]}

nan

^{[1]}시스템에서 보다 복잡하고 불확실한 비선형 함수에 대해 본 논문에서는 보상을 위해 단일 은닉층 신경망을 사용하고 동적 이득을 결합하여 내결함성 제어를 구현했습니다.

^{[2]}

## complex uncertain environment 복잡하고 불확실한 환경

However, traditional FMEA methods have limitations in managing the complex uncertain environment as well as the aggregation and weight allocation of FMEA attributes.^{[1]}Reinforcement Learning (RL) has demonstrated a great potential for automatically solving decision-making problems in complex uncertain environments.

^{[2]}

## complex uncertain triple 복합 불확실 트리플

In this work, we study the lacunary I -statistical convergence concept of complex uncertain triple sequence.^{[1]}The main aim of this article is to introduce the notion of statistical convergence of a complex uncertain triple sequence.

^{[2]}