Machine learning techniques in additive manufacturing: a state of the art review on design, processes and production control

S Kumar, T Gopi, N Harikeerthana, MK Gupta… - Journal of Intelligent …, 2023 - Springer
For several industries, the traditional manufacturing processes are time-consuming and
uneconomical due to the absence of the right tool to produce the products. In a couple of …

African vultures optimization algorithm: A new nature-inspired metaheuristic algorithm for global optimization problems

B Abdollahzadeh, FS Gharehchopogh… - Computers & Industrial …, 2021 - Elsevier
Metaheuristics play a crucial role in solving optimization problems. The majority of such
algorithms are inspired by collective intelligence and foraging of creatures in nature. In this …

Separable multi-innovation Newton iterative modeling algorithm for multi-frequency signals based on the sliding measurement window

L Xu - Circuits, Systems, and Signal Processing, 2022 - Springer
Signal modeling is an important technique in many engineering applications. This paper is
concerned about signal modeling problem for the sine multi-frequency signals or periodic …

Two‐stage gradient‐based iterative algorithms for the fractional‐order nonlinear systems by using the hierarchical identification principle

J Wang, Y Ji, X Zhang, L Xu - International Journal of Adaptive …, 2022 - Wiley Online Library
This article focuses on the parameter estimation issues for a fractional‐order nonlinear
system with autoregressive noise. In the process, the challenge and difficulty are to identify …

Joint two‐stage multi‐innovation recursive least squares parameter and fractional‐order estimation algorithm for the fractional‐order input nonlinear output‐error …

C Hu, Y Ji, C Ma - International Journal of Adaptive Control and …, 2023 - Wiley Online Library
This paper mainly investigates the issue of parameter identification for the fractional‐order
input nonlinear output error autoregressive (IN‐OEAR) model. In order to avoid the problem …

Iterative parameter and order identification for fractional‐order nonlinear finite impulse response systems using the key term separation

J Wang, Y Ji, C Zhang - … Journal of Adaptive Control and Signal …, 2021 - Wiley Online Library
This article considers the parameter estimation for a fractional‐order nonlinear finite impulse
response system with colored noise. For the fractional‐order systems, the challenge and …

DeepYield: A combined convolutional neural network with long short-term memory for crop yield forecasting

K Gavahi, P Abbaszadeh, H Moradkhani - Expert Systems with Applications, 2021 - Elsevier
Crop yield forecasting is of great importance to crop market planning, crop insurance,
harvest management, and optimal nutrient management. Commonly used approaches for …

MR‐DCAE: Manifold regularization‐based deep convolutional autoencoder for unauthorized broadcasting identification

Q Zheng, P Zhao, D Zhang… - International Journal of …, 2021 - Wiley Online Library
Nowadays, radio broadcasting plays an important role in people's daily life. However,
unauthorized broadcasting stations may seriously interfere with normal broadcastings and …

A reduced-order adaptive state observer for DC–DC converters with unknown constant power load

W He, X Wang, MM Namazi, W Zhou… - Control Engineering …, 2024 - Elsevier
In this paper, main objective is to develop a reduced-order adaptive state observer (RASO)
for a large class of DC–DC converters with constant power load (CPL) to estimate their …

Hierarchical recursive least squares algorithms for Hammerstein nonlinear autoregressive output‐error systems

Z Kang, Y Ji, X Liu - … Journal of Adaptive Control and Signal …, 2021 - Wiley Online Library
This article considers the parameter estimation problem of Hammerstein nonlinear
autoregressive output‐error systems with autoregressive moving average noises. Applying …