Results 161 to 170 of about 6,414 (217)

Forecasting photovoltaic power in high-latitude regions via support vector machine optimized by meta-heuristics. [PDF]

Sci Rep
Oruç S, Hınıs MA, Tuğrul T.
europepmc   +1 more source

Intelligent carbon price prediction system based on improved secondary decomposition and multi-head attention bidirectional long short-term memory (BiLSTM) model. [PDF]

Sci Rep
Chen Y.
europepmc   +1 more source

Evaluation of Multiple Influences on the Unconfined Compressive Strength of Fibre-Reinforced Backfill Using a GWO-LGBM Model. [PDF]

Materials (Basel)
Chen X, Wang Y, Miao S, Zhang S, Yu Z, Du L.   +5 more
europepmc   +1 more source

A Novel Gudermannian Function-Driven Controller Architecture Optimized by Starfish Optimizer for Superior Transient Performance of Automatic Voltage Regulation. [PDF]

Biomimetics (Basel)
Izci D, Ekinci S, Jabari M, Kocaman B, Güneş BB, Adas E, Ahmad MA.   +6 more
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Smart room occupancy detection using neural networks and the puma optimization algorithm. [PDF]

Sci Rep
El-Kenawy EM, Zaki AM, Mattar EA, Alhussan AA, Khafaga DS, Eid MM, El-Seddek M.   +6 more
europepmc   +1 more source

Engineering oriented shape optimization of GHT-Bézier developable surfaces using a meta heuristic approach with CAD/CAM applications. [PDF]

Sci Rep
BiBi S, Misro MY, Abbas M, Birhanu A, Miura KT, Wahab MNA, Mahmoud EE.   +6 more
europepmc   +1 more source

Robust Current Sensing in Rectangular Conductors: Elliptical Hall-Effect Sensor Array Optimized via Bio-Inspired GWO-BP Neural Network. [PDF]

Sensors (Basel)
Tang Y, Lu J, Shen Y.
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GWO-RF: A Grey Wolf Optimized Random Forest Model for Predicting Employee Turnover

Informatica
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Real-time congestion control using cascaded LSTM deep neural networks for deregulated power markets.

Sci Rep
Mohan GM, Kumar TA, Srujana A, Fouad Y, Mikhaylov A, Kitmo, Reddy CR.   +6 more
europepmc   +1 more source

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R-GWO: Representative-based grey wolf optimizer for solving engineering problems

Applied Soft Computing, 2021
Abstract The grey wolf optimizer (GWO) is a well-known nature-inspired algorithm, which shows a sufficient performance for solving various optimization problems. However, it suffers from low exploration and population diversity because its optimization process is only based on the best three wolves greedily, and the information of other wolves does ...
Mahdis Banaie-Dezfouli, Mohammad H. Nadimi-Shahraki, Zahra Beheshti   +2 more
openaire   +1 more source