Search results for "fuzzy number"
showing 10 items of 86 documents
Improving stock index forecasts by using a new weighted fuzzy-trend time series method
2017
Define a new technical indicator for measuring the trend of the fuzzy time series.Introduce a new weighted fuzzy-trend time series method to forecast stock indices.Compare ex-post performances of weighted FTS methods using stock market indices.Assess statistical significance of ex-post forecast accuracy for weighted FTS methods. We propose using new weighted operators in fuzzy time series to forecast the future performance of stock market indices. Based on the chronological sequence of weights associated with the original fuzzy logical relationships, we define both chronological-order and trend-order weights, and incorporate our proposals for the ex-post forecast into the classical modeling…
Introducing a Fuzzy-Pattern Operator in Fuzzy Time Series
2017
In this paper we introduce a fuzzy pattern operator and propose a new weighting fuzzy time series strategy for generating accurate ex-post forecasts. A decision support system is built for managing the weights of the information provided by the historical data, under a fuzzy time series framework. Our procedure analyzes the historical performance of the time series using different experiments, and it classifies the characteristics of the series through a fuzzy operator, providing a trapezoidal fuzzy number as one-step ahead forecast. We also present some numerical results related to the predictive performance of our procedure with time series of financial data sets.
Fault detection for nonlinear networked systems based on quantization and dropout compensation: An interval type-2 fuzzy-model method
2016
Abstract This paper investigates the problem of filter-based fault detection for a class of nonlinear networked systems subject to parameter uncertainties in the framework of the interval type-2 (IT2) T–S fuzzy model-based approach. The Bernoulli random distribution process and logarithm quantizer are used to describe the measurement loss and signals quantization, respectively. In the framework of the IT2 T–S fuzzy model, the parameter uncertainty is handled by the membership functions with lower and upper bounds. A novel IT2 fault detection filter is designed to guarantee the residual system to be stochastically stable and satisfy the predefined H ∞ performance. It should be mentioned that…
Forecasting portfolio returns using weighted fuzzy time series methods
2016
We propose using weighted fuzzy time series (FTS) methods to forecast the future performance of returns on portfolios. We model the uncertain parameters of the fuzzy portfolio selection models using a possibilistic interval-valued mean approach, and approximate the uncertain future return on a given portfolio by means of a trapezoidal fuzzy number. Introducing some modifications into the classical models of fuzzy time series, based on weighted operators, enables us to generate trapezoidal numbers as forecasts of the future performance of the portfolio returns. This fuzzy forecast makes it possible to approximate both the expected return and the risk of the investment through the value and a…
Optimal control of discrete-time interval type-2 fuzzy-model-based systems with D-stability constraint and control saturation
2016
This paper investigates the optimal control problem for discrete-time interval type-2 (IT2) fuzzy systems with pole constraints. An IT2 fuzzy controller is characterized by two predefined functions, and the membership functions and the premise rules of the IT2 fuzzy controller can be chosen freely. The pole assignment is considered, which is constrained in a presented disk region. Based on Lyapunov stability theory, sufficient conditions of asymptotic stability with an H ∞ performance are obtained for the discrete-time IT2 fuzzy model based (FMB) system. Based on the criterion, the desired IT2 state-feedback controller is designed to guarantee that the closed-loop system is asymptotically s…
Project portfolio selection and planning with fuzzy constraints
2018
Abstract Selecting a project portfolio is a complex process involving many factors and considerations from the time it is proposed to the time the project portfolio is finally selected. Given that making a good selection is of crucial importance, it is essential to develop well-founded mathematical models to lead the organization to its final goal. To achieve this, such models have to reflect as closely as possible both the real situation of the organization as well as its targets and preferences. However, since the process of selecting and implementing project portfolios occurs in real environments and not in laboratories, uncertainty and a lack of knowledge regarding some data is always a…
A fuzzy ranking strategy for portfolio selection applied to the Spanish stock market
2007
In this paper we present a fuzzy ranking procedure for the portfolio selection problem. The uncertainty on the returns of each portfolio is approximated by means of a trapezoidal fuzzy number. The expected return and risk of the portfolio are then characteristics of that fuzzy number. A rank index that accounts for both expected return and risk is defined, allowing the decision-maker to compare different portfolios. The paper ends with an application of that fuzzy ranking strategy to the Spanish stock market.
Fuzzy Portfolio Selection Models: A Numerical Study
2012
In this chapter we analyze the numerical performance of some possibilistic models for selecting portfolios in the framework of risk-return trade-off. Portfolio optimization deals with the problem of how to allocate wealth among several assets, taking into account the uncertainty involved in the behavior of the financial markets. Different approaches for quantifying the uncertainty of the future return on the investment are considered: either assuming that the return on every individual asset is modeled as a fuzzy number or directly measuring the uncertainty associated with the return on a given portfolio. Conflicting goals representing the uncertain return on and risk of a fuzzy portfolio a…
Fuzzy control of pH using NAL
1991
Abstract A fuzzy controller for a neutralization process is described. The controller was set up for a laboratory pilot plant. The approach is shown to be effective and can be extended to highly nonlinear and nonstationary processes. The “operator” knowledge encoded in the rules was obtained by several experimental runs of the system using manual control. Rules are composed using the max-min compositional rule of inference. The use of metarules, which depends on controller performance and on active disturbances, makes the controller behave like an adaptive controller. The control program is encoded in NAL, a new experimental logic programming language that was first used in this work in a r…
Conditioning on MV-algebras and additive measures —I
1997
Abstract We present a lattice-ordered semigroup approach for the foundation of conditional events which covers the special situations where the underlying (unconditional) events are Boolean or fuzzy, respectively. Our proposal is quite different from other, ring theoretical, approaches. The problem of extending additivity of uncertainty measures from unconditional to conditional events will be discussed.