A software framework for predicting the maize yield using modified multi-layer perceptron
S Ahmed - Sustainability, 2023 - mdpi.com
Predicting crop yields is one of agriculture's most challenging issues. It is crucial in making
national, provincial, and regional choices and estimates the government to meet the food …
national, provincial, and regional choices and estimates the government to meet the food …
Data driven of underground water level using artificial intelligence hybrid algorithms
M Rahimi, H Ebrahimi - Scientific Reports, 2023 - nature.com
As the population grows, industry and agriculture have also developed and water resources
require quantitative and qualitative management. Currently, the management of water …
require quantitative and qualitative management. Currently, the management of water …
Physics-integrated neural differentiable (PiNDiff) model for composites manufacturing
Various manufacturing technologies are being developed to improve the manufacturing of
composites owing to their low weight and high performance. The mechanical properties of …
composites owing to their low weight and high performance. The mechanical properties of …
Influence of different vulcanizing agents on structures and properties of sepiolite-filled natural rubber composites
This study aimed to explore the best cross-link agent for preparing natural rubber (NR)
composites containing sepiolite as filler. Three types of vulcanizing agents, namely, sulfur …
composites containing sepiolite as filler. Three types of vulcanizing agents, namely, sulfur …
Application of generalized regression neural network and Gaussian process regression for modelling hybrid micro-electric discharge machining: a comparative study
Micro-Electric Discharge Machining (μ-EDM) is one of the widely applied
micromanufacturing processes. However, it has several limitations, such as a low cutting …
micromanufacturing processes. However, it has several limitations, such as a low cutting …
Regional application of generalized regression neural network in ionosphere spatio-temporal modeling and forecasting
We propose using the generalized regression neural network (GRNN) method for spatio-
temporal modeling of ionosphere total electron content (TEC). The GRNN model uses radial …
temporal modeling of ionosphere total electron content (TEC). The GRNN model uses radial …
Probabilistic physics-integrated neural differentiable modeling for isothermal chemical vapor infiltration process
Chemical vapor infiltration (CVI) is a widely adopted manufacturing technique used in
producing carbon-carbon and carbon-silicon carbide composites. These materials are …
producing carbon-carbon and carbon-silicon carbide composites. These materials are …
Real-time temperature control in rubber extrusion lines: a neural network approach
In rubber extrusion, precise temperature control is critical due to the process's sensitivity to
fluctuating parameters like compound behavior and batch-specific material variations. Rapid …
fluctuating parameters like compound behavior and batch-specific material variations. Rapid …
Robotics and Automation in Rubber Vulcanization Processes
JG Tejani - Robotics Xplore: USA Tech Digest, 2024 - hal.science
According to this research, automation in rubber vulcanization processes improves
productivity, accuracy, and sustainability. The main goals are to assess robotic integration's …
productivity, accuracy, and sustainability. The main goals are to assess robotic integration's …
[HTML][HTML] Sensitivity analysis: A tool for tailoring environmentally friendly materials
D Seidl, I Ružiak, ZK Jančíková, P Koštial - Expert Systems with …, 2022 - Elsevier
In this article, we examine the use of sensitivity analysis for the optimization of selected
physical properties in rubber compounds and determine objective criteria which allow for the …
physical properties in rubber compounds and determine objective criteria which allow for the …