GA and PSO hybrid algorithm for ANN training with application in Medical Diagnosis

Yadav, Rajesh Kumar; Anubhav,

doi:10.1109/icds47004.2019.8942375

Cited by 15 publications

(6 citation statements)

References 20 publications

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“…BP neural network is used to adjust the weights and thresholds of the network by using the steepest descent method so as to minimize the sum of squares of the network errors. In the subsequent experiments, genetic algorithm (GA) and particle swarm optimization (PSO) will be used to optimize the weights and thresholds of each layer of BP neural network [ 31 , 32 , 33 , 34 ], which can improve the prediction accuracy of BP neural network. At present, the biggest challenge is the random electromagnetic interference in the environment and the random change of ambient temperature, which may lead to a great difference between the inversion result and the actual temperature of the target.…”

Section: Discussionmentioning

confidence: 99%

Design and Implementation of a Novel Interferometric Microwave Radiometer for Human Body Temperature Measurement

Sun

Liu

et al. 2021

Sensors

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In this paper, the key technology of interferometric microwave thermometer is studied, the research can be applied to the temperature measurement of human body and subcutaneous tissue. This paper proposes a hardware architecture of interferometric microwave thermometer with 2 GHz bandwidth, in which the phase shifter is used to correct phase error and the quadrature demodulator is used to realize autocorrelation detection function. The results show that when input power is 7 dBm, the detection sensitivity can reach 176.54 mV/dBm and the temperature resolution of the microwave radiometer can reach 0.4 K. Correction algorithm is designed to improve the accuracy of temperature measurement. After correction, the phase error is reduced from 40° to 1.4° and when temperature changes 0.1 °C, the voltage value changes obviously. Step-by-step calibration and overall calibration are used to calibrate the device. Inversion algorithm can determine the relationship between physical temperature and output voltage. The mean square error of water temperature inversion by multiple linear regression algorithm is 0.607 and that of BP neural network algorithm is 0.334. The inversion accuracy can be improved by reducing the temperature range. Our work provides a promising realization of accurate, rapid and non-contact detection device of human body temperature.

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Section: Discussionmentioning

confidence: 99%

Design and Implementation of a Novel Interferometric Microwave Radiometer for Human Body Temperature Measurement

Sun

Liu

et al. 2021

Sensors

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“…The hidden layer accepts the input data and processes it using an activation function in forward propagation. The activation function is responsible for making a neural network non-linear [19]. The tangent, hyperbolic, sigmoid, and linear functions are commonly chosen activation functions [20].…”

Section: Methodsmentioning

confidence: 99%

PSO-ANN in preventing traffic collisions: a comparative study

Ashikuzzaman

Akram

Anik

et al. 2021

IJEECS

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Traffic accident is a global threat which causes health and economic casualties all around the world. Due to the expansion of transportation systems, congestion can lead to spike road accident. Every year thousands of people have died due to traffic accidents. Various technologies have been adopted by modern cities to minimize traffic accidents. Therefore, to ensure people’s safety, the concept of the smart city has been introduced. In a smart city, factors like road, light, and weather conditions are important to consider to predict traffic mishap. Several machine learning models have been implemented in the existing literature to determine and predict traffic collision. But the accuracy is not enough and there exist a lot of challenges in determining the accident. In this paper, an approach of particle swarm optimization with artificial neural network (PSO-ANN) has been proposed to determine traffic collision using the dataset of the transport department of United Kingdom. The performance of PSO-ANN outperforms the existing machine learning model. PSO-ANN model can be adopted in the transportation system to counter traffic accident issues. Random Forest, Naıve Bayes, Nearest Centroid, K-Nearest Neighbor classification have been used to compare with the proposed PSO-ANN model.

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“…Many variations of the PSO algorithm were proposed over time, including a hybrid PSO and gradientbased algorithm known as PSO-BP [28], which adds a gradient descent component to the swarm framework. This strategy came particularly handy when applying the method to train neural networks since all partial gradients can be computed efficiently by backpropagation.…”

Section: Particle Swarm Optimizationmentioning

confidence: 99%

PSO-PINN: Physics-Informed Neural Networks Trained with Particle Swarm Optimization

Davi¹,

Braga-Neto²

2022

Preprint

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Physics-informed neural networks (PINNs) have recently emerged as a promising application of deep learning in a wide range of engineering and scientific problems based on partial differential equation models. However, evidence shows that PINN training by gradient descent displays pathologies and stiffness in gradient flow dynamics. In this paper, we propose the use of a hybrid particle swarm optimization and gradient descent approach to train PINNs. The resulting PSO-PINN algorithm not only mitigates the undesired behaviors of PINNs trained with standard gradient descent, but also presents an ensemble approach to PINN that affords the possibility of robust predictions with quantified uncertainty. Experimental results using the Poisson, advection, and Burgers equations show that PSO-PINN consistently outperforms a baseline PINN trained with Adam gradient descent.Preprint. Under review.

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GA and PSO hybrid algorithm for ANN training with application in Medical Diagnosis

Cited by 15 publications

References 20 publications

Design and Implementation of a Novel Interferometric Microwave Radiometer for Human Body Temperature Measurement

Design and Implementation of a Novel Interferometric Microwave Radiometer for Human Body Temperature Measurement

PSO-ANN in preventing traffic collisions: a comparative study

PSO-PINN: Physics-Informed Neural Networks Trained with Particle Swarm Optimization

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