Results 71 to 80 of about 34,857 (308)
Forecasting Enrollment Model Based on First-Order Fuzzy Time Series
, 2005 This paper proposes a novel improvement of forecasting approach based on using time-invariant fuzzy time series. In contrast to traditional forecasting methods, fuzzy time series can be also applied to problems, in which historical data are linguistic ...
Konstantin Y., Degtiarev, Sah, Melike
core
Advanced Robotics Research, EarlyView.This work presents a state‐adaptive Koopman linear quadratic regulator framework for real‐time manipulation of a deformable swab tool in robotic environmental sampling. By combining Koopman linearization, tactile sensing, and centroid‐based force regulation, the system maintains stable contact forces and high coverage across flat and inclined surfaces.
Siavash Mahmoudi +2 more
wiley +1 more source
IEEE AccessNon-stationary time series plays a prominent role in the analysis of performance time series of many real-world systems. Recently, fuzzy time series models have been extended to forecast non-stationary time series.
A. J. Saleena +2 more
doaj +1 more source
Fuzzy-Probabilistic Time Series Forecasting Combining Bayesian Network and Fuzzy Time Series Model
SymmetryDespite many fuzzy time series forecasting (FTSF) models addressing complex temporal patterns and uncertainties in time series data, two limitations persist: they do not treat fuzzy and crisp time series as a unified whole for analyzing nonlinear relationships between different moments, and they fail to effectively capture how uncertainty in temporal ...
Bo Wang, Xiaodong Liu
openaire +1 more source
, 2012 Accurate rainfall time series prediction is one of the important tasks in hydrological study. A conventional time series model such as autoregressive moving average or an intelligent model such as artificial neural network have been used efficiently to ...
Kajornrit, J.
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Efficient and Robust Standing Postures of Quadruped Robots
Advanced Robotics Research, EarlyView.A calibrated static framework estimates load, optimizes torques, and adapts posture so quadruped robots stand efficiently and robustly under external payloads, achieving up to 50% lower torque demand. Inspired by the natural posture adjustments of animals under external loading, this article presents an optimization‐based framework for minimizing joint
Mohamad Kanaan +5 more
wiley +1 more source
IEEE Access, 2020 A time series is a sequence of observations that a variable takes with respect to times. It has a wide range of applications in decision making and forecasting in economics, agriculture, medicine, industry, energy sector and other scientific fields. Time
Shahbaz G Hassan +5 more
doaj +1 more source
Fuzzy information granules in time series data
Int. J. Intell. Syst., 2004 Often, it is desirable to represent a set of time series through typical shapes in order to detect common patterns. The algorithm presented here compares pieces of a different time series in order to find such similar shapes. The use of a fuzzy clustering technique based on fuzzy c-means allows us to detect shapes that belong to a certain group of ...
HEIKO HOFER +5 more
openaire +4 more sources
Residual analysis using Fourier series transform in Fuzzy time series model
, 2014 In this paper, we propose a new residual analysis method using Fourier series transform into fuzzy time series model for improving the forecasting performance. This hybrid model takes advantage of the high predictable power of fuzzy time series model and
Tsaur, Ruey-Chyn
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A New Fuzzy Time Series Model Based on Fuzzy C-Regression Model
, 2018 WOS: 000440171900012This study proposes a new fuzzy time series model based on Fuzzy C-Regression Model clustering algorithm (FCRMF). There are two major superiorities of FCRMF in comparison with existing fuzzy time series model based on fuzzy clustering.
Nevin Güler Dincer +1 more
core +1 more source