An Experiment on the Use of Genetic Algorithms for Topology Selection in Deep Learning by Fernando Mattioli, Daniel Caetano, Alexandre Cardoso, Eduardo Naves, Edgard Lamounier

“…The choice of a good topology for a deep neural network is a complex task, essential for any deep learning project. …”
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Real-Time Detection of Milk Adulteration with a Portable Multispectral Analysis Device: A Multispectral Sensor and Optimized Logistic Regression Approach by Mahmut Durgun

“…Utilizing an AS7265x multispectral sensor and Arduino Nano 33 BLE Sense microcontroller, this system employs an optimized logistic regression model to identify starch adulteration in milk samples with near-perfect accuracy. Unlike complex neural network models, the logistic regression model offers simplicity, low power consumption, and efficient operation on microcontrollers. …”
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Text Knowledge Acquisition Method of Collaborative Product Design Based on Genetic Algorithm by Chongyuan Li, Mengmeng Yang

“…After the text knowledge clustering is completed, the text knowledge data of collaborative product design are obtained in an all-around way by using the method of rough set and neural network. The experimental results show that compared with the traditional text knowledge acquisition methods, the clustering effect of the proposed method is better and the text knowledge error is reduced up to 0.02.…”
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Determination of Damage in Reinforced Concrete Frames with Shear Walls Using Self-Organizing Feature Map by Mehdi Nikoo, Łukasz Sadowski, Faezehossadat Khademi, Mohammad Nikoo

“…The obtained model was compared with linear regression (LR) and nonlinear regression (NonLR) models and also the radial basis function (RBF) of a neural network. It was concluded that the SOFM, when optimized with the GA, has more strength, flexibility, and accuracy.…”
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A Novel Faults Diagnosis Method for Rolling Element Bearings Based on ELCD and Extreme Learning Machine by Mingliang Liang, Dongmin Su, Daidi Hu, Mingtao Ge

“…Experimental results show that the proposed method achieved better performance than support vector machine (SVM) and backpropagation (BP) neural network methods.…”
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Logistics Information Traceability Mechanism of Fresh E-Commerce Based on Image Recognition Technology by Xin Zhang, Pengfei Shao

“…Based on the dimensional features and regional-pixel similarity factor, it is verified using the deep neural network. This learning process identifies dimensional variations due to logistics displacement and position suppressing the similarity variations. …”
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An Application of ANN Ensemble for Estimating of Precipitation Using Regional Climate Models by Dongwoo Jang

“…In this study, the precipitation of five regional climate models and actual observed precipitation provided in Korea are applied to ANN (artificial neural network), which suggests ways to improve prediction accuracy for precipitation. …”
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Developing a Travel Time Estimation Method of Freeway Based on Floating Car Using Random Forests by Juan Cheng, Gen Li, Xianhua Chen

“…Compared with the BP (Back Propagation) neural network model and the quadratic polynomial regression model, the proposed Random Forests model is more accurate, and the variables contained in the model are more abundant.…”
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Infrared Thermal Image Gender Classifier Based on the Deep ResNet Model by Alyaa J. Jalil, Naglaa M. Reda

“…The proposed approach has been compared with convolutional neural network (CNN), principal component analysis (PCA), local binary pattern (LBP), and scale invariant feature transform (SIFT). …”
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Self-Attention Multilayer Feature Fusion Based on Long Connection by Chu Yuezhong, Wang Jiaqing, Liu Heng

“…Feature fusion is an important part of building high-precision convolutional neural networks. In the field of image classification, though widely used in processing multiscale features of the same layer and short connections in the same receptive field, feature fusion is rarely used in long connection operations across receptive fields. …”
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Optimization Design and Experimental Study of Low-Pressure Axial Fan with Forward-Skewed Blades by Li Yang, Ouyang Hua, Du Zhao-Hui

“…Using back propagation (BP) neural network and genetic algorithm (GA), the optimization was performed for a radial blade. …”
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The Inverse Solution Algorithm and Trajectory Error Analysis of Robotic Arm Based on MQACA-RBF Network by Xu Cheng, Ming Zhao

“…This algorithm establishes the prediction model through the neural network and uses the quantum ant colony algorithm to optimize the output weight. …”
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Implementation of a low‐power LVQ architecture on FPGA by Najoua Chalbi, Mohamed Boubaker, Mohamed Hedi Bedoui

“…This study presents an architecture‐optimising methodology for embedding an learning vector quantization (LVQ) neural network on an field programmable gate array (FPGA) device. …”
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Complexity Analysis of a Four-Dimensional Energy-Economy-Environment Dynamic System by Shuai Jin, Liuwei Zhao

“…Based on the official data, the Levenberg–Marquardt backpropagation neural network method was optimized by genetic algorithm to effectively identify the parameters in the 3E system. …”
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EFFICIENT RETINAL IMAGE SEGMENTATION BY U-NET FOR AGE-RELATED MACULAR DEGENERATION DIAGNOSIS by S Sujatha, Pramod Pandey, D Gnana Rajesh

“…It is a specialized convolutional neural network that has shown significant potential in accurately segmenting intricate structures captured in medical images. …”
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Expression Recognition Method Using Improved VGG16 Network Model in Robot Interaction by Shengbin Wu

“…Then, the high-dimensional abstract feature data output by the improved VGG16 is input into the convolution neural network (CNN) for training, so as to output the expression types with high accuracy. …”
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Model Calibration and Validation for the Fuzzy-EGARCH-ANN Model by Geleta T. Mohammed, Jane A. Aduda, Ananda O. Kube

“…This work shown as the fuzzy-EGARCH-ANN (fuzzy-exponential generalized autoregressive conditional heteroscedastic-artificial neural network) model does not require continuous model calibration if the corresponding DE algorithm is used appropriately, but other models such as GARCH, EGARCH, and EGARCH-ANN need continuous model calibration and validation so they fit the data and reality very well up to the desired accuracy. …”
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Anomaly Detection in Moving Crowds through Spatiotemporal Autoencoding and Additional Attention by Biao Yang, Jinmeng Cao, Rongrong Ni, Ling Zou

“…We propose an anomaly detection approach by learning a generative model using deep neural network. A weighted convolutional autoencoder- (AE-) long short-term memory (LSTM) network is proposed to reconstruct raw data and perform anomaly detection based on reconstruction errors to resolve the existing challenges of anomaly detection in complicated definitions and background influence. …”
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Research on the Application of Deep Learning Methods in the Field of Image Classification by Peng Yuhui

“…The application of deep learning methods such as Convolutional Neural Network, Recurrent Neural Networks and Long Short-Term Memory in image classification is also discussed. …”
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Feature Extraction and Classification of Music Content Based on Deep Learning by Qianqiu Shi, Young Chun Ko

“…The improved depth confidence network identifies and classifies Chinese traditional musical instruments through Softmax layer, and the accuracy is even as high as 99.2%; DBN is combined with Softmax neural network algorithm when only a few labeled samples in the training set are used for network fine-tuning, and the accuracy of the algorithm can still reach more than 90%, which can reduce the workload in the early stage. …”
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