A q-Gradient Descent Algorithm with Quasi-Fejér Convergence for Unconstrained Optimization Problems

Mishra, Shashi Kant; Rajković, Predrag M.; Samei, Mohammad Esmael; Chakraborty, Suvra Kanti; Ram, Bhagwat; Kaabar, Mohammed K. A.

doi:10.3390/fractalfract5030110

Cited by 10 publications

(2 citation statements)

References 48 publications

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“…Optimization problem is an applied technique based on mathematics for solving various optimization problems [17]. It is widely used in image processing, pattern recognition, automatic control and signal processing and other fields.…”

Section: Intelligent Optimization Algorithmmentioning

confidence: 99%

Optimization of Hyperparameters in Object Detection Models Based on Fractal Loss Function

Zhou

Wang

2022

Fractal Fract

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Hyperparameters involved in neural networks (NNs) have a significant impact on the accuracy of model predictions. However, the values of the hyperparameters need to be manually preset, and finding the best hyperparameters has always puzzled researchers. In order to improve the accuracy and speed of target recognition by a neural network, an improved genetic algorithm is proposed to optimize the hyperparameters of the network by taking the loss function as the research object. Firstly, the role of all loss functions in object detection is analyzed, and a mathematical model is established according to the relationship between loss functions and hyperparameters. Secondly, an improved genetic algorithm is proposed, and the feasibility of the improved algorithm is verified by using complex fractal function and fractional calculus. Finally, the improved genetic algorithm is used to optimize the hyperparameters of the neural network, and the prediction accuracy of the model before and after the improvement is comprehensively analyzed. By comparing with state-of-the-art object detectors, our proposed method achieves the highest prediction accuracy in object detection. Based on an average accuracy rate of 95%, the detection speed is 20 frames per second, which shows the rationality and feasibility of the optimized model.

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Section: Intelligent Optimization Algorithmmentioning

confidence: 99%

Optimization of Hyperparameters in Object Detection Models Based on Fractal Loss Function

Zhou

Wang

2022

Fractal Fract

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“…e differential equation model is an excellent method of describing the process of a system, and it can transform complex social problems into an intuitive mathematical model. At present, mathematicians continue to expand the new field of differential equation research, thus promoting the development of differential equations [20][21][22]. e differential equation model has been widely used in studying epidemic diseases [23][24][25][26][27].…”

Section: Introductionmentioning

confidence: 99%

Evaluation of the Number of Visits to Chinese Medical Institutions Using a Logistic Differential Equation Model

Zhao

Wang

et al. 2021

Complexity

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In this study, we established a two-dimensional logistic differential equation model to study the number of visits in Chinese PHCIs and hospitals based on the behavior of patients. We determine the model's equilibrium points and analyze their stability and then use China medical services data to fit the unknown parameters of the model. Finally, the sensitivity of model parameters is evaluated to determine the parameters that are susceptible to influence the system. The results indicate that the system corresponds to the zero-equilibrium point, the boundary equilibrium point, and the positive equilibrium point under different parameter conditions. We found that, in order to substantially increase visits to PHCIs, efforts should be made to improve PHCI comprehensive capacity and maximum service capacity.

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Introduction to Unconstrained Optimization and Quantum Calculus

Ram,

Mishra,

Lai

et al. 2024

Uncertainty and Operations Research

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A q-Gradient Descent Algorithm with Quasi-Fejér Convergence for Unconstrained Optimization Problems

Cited by 10 publications

References 48 publications

Optimization of Hyperparameters in Object Detection Models Based on Fractal Loss Function

Optimization of Hyperparameters in Object Detection Models Based on Fractal Loss Function

Evaluation of the Number of Visits to Chinese Medical Institutions Using a Logistic Differential Equation Model

Introduction to Unconstrained Optimization and Quantum Calculus

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