Results 141 to 150 of about 129,225 (287)

Machine Learning‐Driven Classification and Production Capacity Prediction of Tight Sandstone Reservoirs: A Case Study of the Taiyuan Formation, Ordos Basin

Energy Science &Engineering, EarlyView.
On the basis of core and log data, a Bayesian‐Optimized Random Forest model achieved 92.76% accuracy in classifying tight sandstone reservoirs. A gray relational analysis‐derived evaluation index shows > 80% consistency with actual gas zones. ABSTRACT Tight sandstone gas (TSG), an unconventional oil–gas resource, has heterogeneous reservoirs ...
Yin Yuan, Haijiao Fu, Detian Yan, Gang Wang, Shuguang Yang, Mengmeng Liu, Qingling Jiang, Xiaoming Wang, Wei Wang   +8 more
wiley   +1 more source

Optimizing Electric Vehicle Charging Scheduling With Deep Q Networks and Long Short‐Term Memory‐Based Electricity and Battery State of Charge Prediction

Energy Science &Engineering, EarlyView.
Schematic diagram showing the proposed approach for EV charging/discharging. ABSTRACT The number of electric vehicles (EVs) on the road is rising as a result of recent advancements in EV technology, and EVs are important to the smart grid economy. Demand response schemes involving electric vehicles have the potential to dramatically reduce the cost of ...
F. Zonuntluanga, Subhasish Deb, Kshetrimayum Robert Singh, Subir Datta, Ahmet Onen, Taha Selim Ustun, Jaesung Jung   +6 more
wiley   +1 more source

Real‐Time Data‐Driven Fault Diagnosis of Photovoltaic Arrays Using an Edge‐Server Machine‐Learning Framework

Energy Science &Engineering, EarlyView.
A real‐time, data‐driven framework detects and classifies photovoltaic array faults using edge sensing and server‐side machine learning. Ensemble tree models achieve near‐perfect accuracy with low latency, enabling practical, low‐cost deployment for reliable PV monitoring and intelligent maintenance.
Premkumar Manoharan, Sowmya Ravichandran, Deepak Kumar Sinha, Chandran Ramakrishnan, Omar Almomani   +4 more
wiley   +1 more source

Energy Consumption and CO2 Emissions Forecasting of Transport Sector Using Machine Learning

Energy Science &Engineering, EarlyView.
The transport sector accounts for approximately one‐quarter of Iran's final energy consumption. The energy demand in this sector has the least variation, with petroleum products accounting for more than 85% of the demand. Furthermore, the accelerated growth of energy consumption and the sector's reliance on fossil fuels, which are the main cause of ...
Amir Hossein Akbari, Seyyed Mohammad Hashemi, Meisam Farajollahi   +2 more
wiley   +1 more source

'Backpropagation and the brain' realized in cortical error neuron microcircuits. [PDF]

PLoS Comput Biol
Max K, Jaras I, Granier A, Wilmes KA, Petrovici MA.   +4 more
europepmc   +1 more source

Decentralized Federated Learning for Wind Turbine Bearing Prognostics Under Data Scarcity and Statistical Heterogeneity

Energy Science &Engineering, EarlyView.
This paper proposes a decentralized peer‐to‐peer federated learning framework for wind turbine bearing remaining useful life prediction, introducing a virtual client paradigm in which statistical health indicators serve as independent feature‐level clients—enabling privacy‐preserving collaborative prognostics from a single physical asset under ...
Jihene Sidhom, Lotfi Saidi, Eric Bechhoefer   +2 more
wiley   +1 more source

Closed-form feedback-free learning with forward projection. [PDF]

Nat Commun
O'Shea R, Rajendran B.
europepmc   +1 more source

Stability Evaluation and Parametric Optimization of Coal‐Concrete Composite Bearing Systems Under Mine‐Water‐Induced Deterioration: Experiments and FEINN Analysis

Energy Science &Engineering, EarlyView.
Mine‐water immersion tests reveal pronounced coal weakening (vs. minor concrete degradation), identifying coal pillars as the stability‐limiting component in composite dams. A coupled FEINN framework quantifies extreme‐pressure stability and ranks multi‐parameter designs via a normalized multi‐indicator scheme, enabling optimized dam configuration for ...
He Wen, Hongchuan Dai, Guixin Zhang, Pengzhe Li, Tong Yang, Cang Gong, Renbo Gao   +6 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

Toxicological Evaluation of the Undesirable Components in Processed Infant Foods Using Artificial Intelligence

Future Postharvest and Food, EarlyView.
The detection of toxins in baby food using artificial intelligence. ABSTRACT Infant foods and baby formulas are becoming increasingly popular across the globe owing to their ease of consumption and nutritional value specific to infants. Impurities may find their way into the food chain at any point from the acquisition of raw materials to final ...
Poornima Singh, Anurag Singh, Ashutosh Upadhyay, Navneet Kumar   +3 more
wiley   +1 more source