Application of computational intelligence methods in agricultural soil–machine interaction: A review

C Badgujar, S Das, DM Figueroa, D Flippo - Agriculture, 2023 - mdpi.com
Rapid advancements in technology, particularly in soil tools and agricultural machinery,
have led to the proliferation of mechanized agriculture. The interaction between such …

Applying a supervised ANN (artificial neural network) approach to the prognostication of driven wheel energy efficiency indices

H Taghavifar, A Mardani - Energy, 2014 - Elsevier
This paper examines the prediction of energy efficiency indices of driven wheels (ie traction
coefficient and tractive power efficiency) as affected by wheel load, slippage and forward …

Artificial neural network based modeling of tractor performance at different field conditions

S Almaliki, R Alimardani, M Omid - … Engineering International: CIGR …, 2016 - cigrjournal.org
Application of tractors in farming is undeniable as a power supply. Therefore, performance
model for evolving parameters of tractors and implements are essential for farm machinery …

Applying an artificial neural network approach to the analysis of tractive properties in changing soil conditions

K Pentoś, K Pieczarka - Soil and Tillage Research, 2017 - Elsevier
For better performance of a micro-tractor during agricultural operations, it is necessary to
select the optimal tractor configuration for the operation. The purpose of this study was to …

Deep neural networks to predict autonomous ground vehicle behavior on slo** terrain field

C Badgujar, S Das, DM Figueroa… - Journal of Field …, 2023 - Wiley Online Library
Conventional large agricultural machinery or implements are unsafe and unsuitable to
operate on slopes> 6∘ 6^∘ or 10%. Tractor rollovers are frequent on slopes, precluding …

On the modeling of energy efficiency indices of agricultural tractor driving wheels applying adaptive neuro-fuzzy inference system

H Taghavifar, A Mardani - Journal of Terramechanics, 2014 - Elsevier
The objective is to assess the potential of adaptive neuro-fuzzy inference system (ANFIS) for
the prediction of energy efficiency indices of driving wheels (ie traction coefficient and …

Use of a convolutional neural network for predicting fuel consumption of an agricultural tractor

H Jalilnezhad, Y Abbaspour-Gilandeh… - Resources, 2023 - mdpi.com
The energy crisis and depleting fossil fuel resources have always been the focus of
researchers. Fuel consumption of agricultural tractors is not an exception. Researchers have …

Evaluating the effect of tire parameters on required drawbar pull energy model using adaptive neuro-fuzzy inference system

H Taghavifar, A Mardani - Energy, 2015 - Elsevier
Determination of the required energy for drawbar pull of agricultural tractors plays a
significant role in the characterization of the quality of tractors during different operations …

A multivariate multiple regression analysis of tire-road contact peak triaxial stress by using machine learning methods

X Li, M Guo, X Zhou - Mechanics of Advanced Materials and …, 2021 - Taylor & Francis
Predicting the tire-road contact triaxial stress is significant in assessing performance of
vehicle and road surface material. However, both the Finite Element Method and the direct …

Prediction of kinematic viscosities of biodiesels derived from edible and non-edible vegetable oils by using artificial neural networks

T Eryilmaz, MK Yesilyurt, A Taner, SA Celik - Arabian Journal for Science …, 2015 - Springer
In the present study, the seeds named as wild mustard (Sinapis arvensis L.) and safflower
(Carthamus tinctorius L.) were used as feedstocks for production of biodiesels. In order to …