Results 91 to 100 of about 11,119,065 (317)

A New Synergistic Forecasting Method for Short-Term Traffic Flow with Event-Triggered Strong Fluctuation

Journal of Control Science and Engineering, 2018
Directing against the shortcoming of low accuracy in short-term traffic flow prediction caused by strong traffic flow fluctuation, a novel method for short-term traffic forecasting based on the combination of improved grey Verhulst prediction algorithm ...
Darong Huang, Zhenping Deng, Bo Mi
doaj   +1 more source

Space-time modeling of traffic flow [PDF]

A key concern in transportation planning and traffic management is the ability to forecast traffic flows on a street network. Traffic flows forecasts can be transformed to obtain travel time estimates and then use these as input to travel demand models ...
Prastacos, Poulicos, Kamarianakis, Yiannis   +1 more
core  

Selection of Significant On−Road Sensor Data for Short−Term Traffic Flow Forecasting Using the Taguchi Method. [PDF]

, 2012
Over the past two decades, neural networks have been applied to develop short-term traffic flow predictors. The past traffic flow data, captured by on-road sensors, is used as input patterns of neural networks to forecast future traffic flow conditions ...
Chan, Kit, Jaipal Singh, T.S. Dillon, V. Palade, J. Singh, Chan, Kit Yan, Palade, Vasile, Elizabeth Chang, S. Khadem, Chan, K.Y., E.Chang, Dillon, Tharam, Khadem, Saghar, Chang, Elizabeth, Saghar Khadem, Dillon, T.S., Tharam S. Dillon, Dillon, Tharam S, Vasile Palade, K.Y. Chan, Palade, V., Singh, Jaipal, Khadem, S., Singh, J., Kit Yan Chan   +24 more
core   +1 more source

An On‐Demand Neuromorphic Vision System Enabled by a Multi‐Paradigm Neuromorphic Device and Hierarchical Reconfigurability Designed from Device to System Level

Advanced Science, EarlyView.
An on‐demand ultra‐reconfigurable intelligent vision system with hierarchical reconfigurability from device to system levels is demonstrated. Through co‐design of a multi‐paradigm device, reconfigurable circuits, and adaptive system architecture/algorithms, the system enables seamless switching among spiking, non‐spiking, neuromorphic imaging (NI), and
Biyi Jiang, Jiayi Xu, Liang Ran, Xinhe Feng, Khalil Harrabi, Yida Li, Longyang Lin, Feichi Zhou   +7 more
wiley   +1 more source

An Artificial Neural Network Model for Short-Term Traffic Flow Prediction in Two Lane Highway in Khulna Metropolitan City, Bangladesh

Emerging Technologies and Engineering Journal
Short-term traffic flow prediction is one of the most significant research topics in traffic engineering. It is instrumental in designing a more modern transport network to manage traffic signals and reduce congestion.
Md. Ebrahim Shaik, Monirul Islam, Md. Ripon Kobir, Kazi Furkan   +3 more
doaj   +1 more source

Accurate non-stationary short-term traffic flow prediction method

CoRR, 2022
Precise and timely traffic flow prediction plays a critical role in developing intelligent transportation systems and has attracted considerable attention in recent decades. Despite the significant progress in this area brought by deep learning, challenges remain.
openaire   +2 more sources

Research on the Application of Intelligent Algorithm in Short-Term Traffic Flow Forecast

, 2015
In recent years, with the vigorous development of intelligent transportation systems, traffic control and traffic flow guidance have become popular issue of intelligent transportation systems (ITS). The key issue to achieve traffic control guidance is to
Wang DP(王丹萍), Hu KY(胡琨元), Han Xiaowei   +2 more
core  

Charting Endocrine Progenitors Across Species and Organs

Advanced Science, EarlyView.
Endocrine progenitors give rise to the hormone‐producing cells of the pancreas and intestine. Using single‐cell multiomics and proteomics, this study compares these progenitors across species, systems, and organs, mapping the conserved and species‐specific gene regulatory networks that guide their formation.
Changying Jing, Michael Sterr, Özüm Sehnaz Caliskan, Lama Saber, Nicole Katarina Rogers, Samuel Ogden, Kei Kozawa, Christos Karampelias, Jessica Jaki, Aimée Bastidas‐Ponce, Falk Janos Farkas, Oliver Czarnecki, Osvaldo Rodrigues Pereira, Perla Cota, Valerie Vandenbempt, Diego Balboa, Anika Böttcher, Natalie Krahmer, Mohammad Lotfollahi, Julie B. Sneddon, Heiko Lickert, Mostafa Bakhti   +21 more
wiley   +1 more source

Smart Nanotechnologies for Multimodal Neuromodulation and Brain Interfacing

Advanced Science, EarlyView.
Recent advances in smart nanotechnologies are expanding the toolbox for brain interfacing, from wireless neuromodulation and high‐resolution sensing to targeted delivery within the central nervous system. By combining responsive nanomaterials with bioinspired design, these platforms enable multimodal interactions with neurons and glia, while also ...
Tommaso Curiale, Marie Celine Lefevre, Alessio Carmignani, Maria Cristina Ceccarelli, Matteo Battaglini, Attilio Marino, Gianni Ciofani   +6 more
wiley   +1 more source

Ferroelectric Devices for In‐Memory and In‐Sensor Computing

Advanced Science, EarlyView.
Inspired by biological systems, in‐memory and in‐sensor computing overcome von Neumann bottlenecks. Ferroelectric devices can mimic synaptic functions and sense stimuli like light or force, therefore are ideal for these paradigms. This review introduces the ferroelectric devices applied for in‐memory and in‐sensor computing, covering their structures ...
Hong Fang, Ronghuan Xie, Qiang Cao, Shishen Yan, Xiaolin Wang, Limei Zheng   +5 more
wiley   +1 more source