A Dynamic Fuzzy Cluster Algorithm for Time Series
Abstract and Applied Analysis, 2013 This paper presents an efficient algorithm, called dynamic fuzzy cluster (DFC), for dynamically clustering time series by introducing the definition of key point and improving FCM algorithm.
Min Ji, Fuding Xie, Yu Ping
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An AI‐Enabled All‐In‐One Visual, Proximity, and Tactile Perception Multimodal Sensor
Advanced Robotics Research, EarlyView.Targeting integrated multimodal perception of robots, an AI‐enabled all‐in‐one multimodal sensor is proposed. This sensor is capable of perceiving three types of modalities, including vision, proximity, and tactility. By toggling an ultraviolet light and adjusting the camera focus, it switches smoothly between multiple perceptual modalities, enabling ...
Menghao Pu +7 more
wiley +1 more source
Pythagorean fuzzy time series model based on Pythagorean fuzzy c-means and improved Markov weighted in the prediction of the new COVID-19 cases [PDF]
Soft comput, 2021 Xian S, Cheng Y.
europepmc +2 more sources
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
From Lab to Landscape: Environmental Biohybrid Robotics for Ecological Futures
Advanced Robotics Research, EarlyView.This Perspective explores environmental biohybrid robotics, integrating living tissues, microorganisms, and insects for operation in real‐world ecosystems. It traces the leap from laboratory experiments to forests, wetlands, and urban environments and discusses key challenges, development pathways, and opportunities for ecological monitoring and ...
Miriam Filippi
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STOCK PRICE FORECASTING USING FUZZY C-MEANS AND TYPE-2 FUZZY TIME SERIES
BarekengStock prices have unstable movements, so forecasting is needed to decide to invest appropriately according to the strategy. Fuzzy Time Series (FTS) uses fuzzy sets to forecast future time series values using historical data.
Rineka Brylian Akbar Satriani +2 more
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A New Time-Invariant Fuzzy Time Series Forecasting Method Based on Genetic Algorithm
Advances in Fuzzy Systems, 2012 In recent years, many fuzzy time series methods have been proposed in the literature. Some of these methods use the classical fuzzy set theory, which needs complex matricial operations in fuzzy time series methods.
Erol Eğrioğlu
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Astrocyte Enrichment of 3D Cortical Constructs Enhances Brain Repair
Advanced Science, EarlyView.This study highlights the role of astrocytes in supporting neural progenitor cell survival and differentiation after traumatic brain injury. Astrocytes enhanced neuronal differentiation, improved cell survival in co‐cultures, and promoted integration of microfluidics‐based implants with host tissue following implantation. Additionally, increased axonal
Elisa M. Cruz +20 more
wiley +1 more source
PERAMALAN INDEKS HARGA SAHAM GABUNGAN (IHSG) DENGAN METODE FUZZY TIME SERIES MARKOV CHAIN
Jurnal MIPA, 2016 Tujuan penelitian ini adalah untuk mengetahui akurasi metode Fuzzy Time Series Markov Chain pada peramalan IHSG dan membuat aplikasi untuk peramalan IHSG menggunakan software MATLAB. Dalam penelitian ini, data bersumber dari yahoo finance. Data historis
Y Aristyani, E Sugiharti
doaj
Prediction of university fund revenue and expenditure based on fuzzy time series with a periodic factor. [PDF]
PLoS One, 2023 Shen Y, Ma X, Sun Y, Du S.
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