A globally convergent neurodynamics optimization model for  mathematical programming with equilibrium constraints

Ezazipour, S.; Golbabai, A.

doi:10.14736/kyb-2020-3-0383

Cited by 3 publications

(3 citation statements)

References 32 publications

(77 reference statements)

Supporting

Mentioning

Contrasting

Order By: Relevance

“…Neural networks and ANFIS have been used in many fields of engineering, science, economics, and so on 13‐17 . So far, numerous algorithms have been proposed based on neural networks to diagnose different diseases and pests on tomato leaves.…”

Section: Related Workmentioning

confidence: 99%

“…Neural networks and ANFIS have been used in many fields of engineering, science, economics, and so on. [13][14][15][16][17] So far, numerous algorithms have been proposed based on neural networks to diagnose different diseases and pests on tomato leaves. For example, in 2017, Brahimi et al 18 In 2019, Picon et al 21 applied a mobile application to classify four different types of wheat diseases (including Rust, Septoria, Tan Spot, and Other/Healthy) for 8178 images.…”

Section: Related Workmentioning

confidence: 99%

See 1 more Smart Citation

Diagnosis of Alternaria disease and leafminer pest on tomato leaves using image processing techniques

2022

View full text Add to dashboard Cite

BACKGROUND: Diseases such as Alternaria and pests such as leafminer threaten tomato as one of the most widely used agricultural products. These pests and diseases first damage the leaves of tomatoes, then the flowers, and finally the fruit. Therefore, the damage to the tomato tree must be controlled in its early stages. It is difficult for farmers to distinguish Alternaria disease from leafminer pest at the early and middle stages of their outbreak on tomato leaves. In the present study, 272 tomato leaf images were prepared from the farm of the Vali-e-Asr University of Rafsanjan, including 100 healthy leaves and 172 infected leaves with both Alternaria and leafminer at the initial stages. The image processing technique, texture, neural networks and adaptive network-based fuzzy inference system (ANFIS) classifiers were used to diagnose Alternaria disease and leafminer pest on this dataset. RESULTS:The results showed that the ANFIS classifier achieved an accuracy of 84.71% when performing an equal error rate, 87.78% in the area under the curve, and 85.23% in 3.26 s on the central processing unit for the segmentation of Alternaria disease and leafminer pest in RGB color space. Also, the accuracy of 90% and 98% were obtained for segmentation and classification on the PlantVillage dataset in YCBCR color space.CONCLUSION: The present study suggests a high classification accuracy for an intelligent selection of pixel values to train the ANFIS classifier. This classifier has high accuracy and speed, low sensitivity to the light intensity of images, and practical application in diagnosing various diseases and pests on numerous datasets.

show abstract

Section: Related Workmentioning

confidence: 99%

Section: Related Workmentioning

confidence: 99%

Diagnosis of Alternaria disease and leafminer pest on tomato leaves using image processing techniques

2022

View full text Add to dashboard Cite

show abstract

“…With the development of neural grid and machine learning models (Jain et al, 2021 ; Mohan et al, 2021 ; Gupta et al, 2021 ), traditional evaluation methods (principal component analysis (Ezazipour and Golbabai, 2020 ), fuzzy comprehensive evaluation (Wold et al, 1987 ), hierarchical analysis (Bing et al, 2010 ), and entropy weight method (Ho, 2008 ) and the introduction of the comprehensive evaluation system of the machine learning method have become a hot research topic.…”

Section: Literature Reviewmentioning

confidence: 99%

An artificial intelligence method for comprehensive evaluation of preschool education quality

Niu

2022

Front. Psychol.

View full text Add to dashboard Cite

The evolution in the quality of teaching for preschool education is worth studying. In this article, we solved the qualitative problems in the comprehensive quality evaluation by suggesting a method of quantitative combination and establishing a set of indicators suitable for the comprehensive quality evaluation of students in the kindergarten. According to the experience summed up by previous scholars, the weight of each index is obtained by an analytic hierarchy process. This study analyzed the defects and causes of fuzzy comprehensive evaluation and the neural network model in the construction of early childhood and preschool education's comprehensive quality evaluation model and propose a Feedforward Neural Network (FNN) model. FNN combined with neural network (NN) and fuzzy logic characteristics introduces fuzzy concepts and fuzzy inference rules into neural networks of neurons, the connection power, and network learning. It improves the learning ability of NN and fuzzy evaluation of the power of expression and effectively exerts the advantages of fuzzy logic and neural network to make up for their shortcomings. However, the convergence speed is very slow. To solve this problem, the similarity measure was used to improve the number of hidden layer nodes of the network. The effectiveness and feasibility of the FNN improved hidden layer nodes are verified by an example so as to realize the automation of comprehensive quality evaluation.

show abstract

The use of artificial neural networks to diagnose Alzheimer’s disease from brain images

Fouladi

Safaei

Arshad

et al. 2022

Multimed Tools Appl

View full text Add to dashboard Cite

A globally convergent neurodynamics optimization model for mathematical programming with equilibrium constraints

Abstract: Institute of Mathematics of the Czech Academy of Sciences provides access to digitized documents strictly for personal use. Each copy of any part of this document must contain these Terms of use.

Cited by 3 publications

References 32 publications

Diagnosis of Alternaria disease and leafminer pest on tomato leaves using image processing techniques

Diagnosis of Alternaria disease and leafminer pest on tomato leaves using image processing techniques

An artificial intelligence method for comprehensive evaluation of preschool education quality

The use of artificial neural networks to diagnose Alzheimer’s disease from brain images

Contact Info

Product

Resources

About