Results 121 to 130 of about 27,097 (268)

DETERMINATION OF THE NEXT STOPPING FLOOR IN ELEVATOR TRAFFIC CONTROL BY MEANS OF NEURAL NETWORKS

Electrica, 2005
When a group of lifts serve together it is important coordinate the movements of the individual lifts in such a way that the lift group should operate efficiently.
C.Erdem İMRAK, Mustafa ÖZKIRIM
doaj  

An algorithm for seizure detection in rodents

Epilepsia Open, EarlyView.
Abstract Objective Epilepsy animal research often relies on long‐term intracranial electroencephalographic (iEEG) recordings. Here, we describe an artificial neural network (ANN) algorithm for automatic detection of seizures. Methods The algorithm was trained on iEEG recordings of three mouse models of chronic epilepsy: (1) the pilocarpine model of ...
Lyna Kamintsky, Gerben van Hameren, Itai Weissberg, Pooyan Moradi, Ofer Prager, Alaa Abu Ahmad, Lior Schori, Albert Becker, Yaniv Zigel, Alon Friedman   +9 more
wiley   +1 more source

Hybrid Simulation–Machine Learning Surrogates for Coordinate‐Based Solar and Wind Energy Yield Assessment in Iraq: A Streamlit Decision‐Support Tool

Energy Science &Engineering, EarlyView.
This study integrates climatic simulations with machine learning to predict solar and wind energy across Iraq. Results show Random Forest excels for solar (R2 = 0.98) and neural networks for wind (R2 = 0.97), enabling a practical web tool for renewable energy planning. ABSTRACT Driven by the global shift away from fossil fuels, solar and wind resources
Bassam Musheer Kareem, Abdolsalam Ebrahimpour, Jafar Ghafouri, Roghayyeh Motallebzadeh   +3 more
wiley   +1 more source

Insulator fault feature extraction system of substation equipment based on machine vision

IET Networks, EarlyView., 2022
Abstract The artificial intelligence technology and intelligent automation are more and more widely used, the insulators play a supporting and insulating role in the operation of the grid. The use of machine vision inspection technology to detect insulator faults has become an inevitable trend of the times.
Keruo Jiang, Qiaoqun Xia, Lijun Ma, Xin Xu, Zhipeng Shao   +4 more
wiley   +1 more source

A Probabilistic Fractional Order Physics Informed Mamba Kolmogorov‐Arnold Network for State‐of‐Charge Estimation in Grid‐Connected Battery Energy Storage Systems

Energy Science &Engineering, EarlyView.
This paper introduces the probabilistic fractional‐order Mam‐KAN (PFO‐Mam‐KAN) controller, a physics‐informed gray‐box framework for real‐time battery state‐of‐charge estimation. By unifying efficient Mamba encoders with uncertainty‐aware fractional physics, it achieves superior 0.31% RMSE accuracy and robust grid‐support operation under dynamic ...
Arun Kumar Rawat, Subhash Chandra, Vinay Kumar Deolia   +2 more
wiley   +1 more source

Beta Forecasting With Realized Beta Estimators and Machine Learning Algorithms

Journal of Forecasting, EarlyView.
ABSTRACT This paper applies machine learning algorithms to the modeling of realized betas for the purposes of forecasting stock systematic risk. Higher levels of beta forecast accuracy are demonstrated, relative to other studies in the literature. These improvements are also highly significant, both statistically and economically.
Bao Doan, Dulani Jayasuriya, John B. Lee, Jonathan J. Reeves   +3 more
wiley   +1 more source

Harnessing the Potential of LLMs in Hospital Management: Insights Into Medical Data Inquiry

The International Journal of Health Planning and Management, EarlyView.
ABSTRACT Background Considering the rapid expansion of hospital operations and the increasing digitisation of medical data, there is a pressing need for efficient and intelligent methods to process and analyse large‐scale medical data. Methods We integrated the QLoRA algorithm with ChatGLM2‐6b, Llama2‐7b, and Llama2‐13b models, fine‐tuning them on a ...
Jiaxi Li, Yu Zhang, Jing Zhao, Shengyang He, Danni Li   +4 more
wiley   +1 more source

Interleaved Diffractive Networks for Information Transfer Through Random Diffusers

Laser &Photonics Reviews, EarlyView.
This work presents a cascaded diffractive optical network that enables information transfer through random, unknown diffusers using passive, interleaved structured layers that mitigate scattering without digital computation. A hybrid optical‐digital version further improves robustness and reconstruction fidelity under distortions, with both simulations
Yuhang Li, Yiyang Wu, Shiqi Chen, Xilin Yang, Aydogan Ozcan   +4 more
wiley   +1 more source

Phase Multiplexed Optical Computing: Reconfiguring a Multi‐Task Diffractive Optical Processor Using Illumination Phase Diversity

Laser &Photonics Reviews, EarlyView.
A monochrome multi‐task diffractive optical network architecture is designed to leverage illumination‐phase multiplexing to dynamically reconfigure its output function and accurately implement a large set of complex‐valued linear transformations between an input and an output aperture.
Xiao Wang, Aydogan Ozcan
wiley   +1 more source

High-Fidelity Backpropagation through Primate Foveal Cones. [PDF]

J Neurosci
Wienbar SR, Bryman GS, Do MTH.
europepmc   +1 more source