An Author Gender Detection Method Using Whale Optimization Algorithm and Artificial Neural Network by Fatemeh Safara, Amin Salih Mohammed, Moayad Yousif Potrus, Saqib Ali, Quan Thanh Tho, Alireza Souri, Fereshteh Janenia, Mehdi Hosseinzadeh

“…Machine learning and meta-heuristic algorithms are valuable techniques to extract hidden patterns useful for detecting gender of a text. In this paper, an artificial neural network (ANN) is employed as a classifier to detect the gender of an email author and the whale optimization algorithm (WOA) is used to find optimal weights and biases for improving the accuracy of the ANN classification. …”
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Application of a dynamic optimization-based multi-attribute fusion method for fault detection. by Chen Ma, Handong Huang, Youcai Tang, Suo Cheng, Chao Wang, Xin Wang

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Technology and Method Optimization for Foot–Ground Contact Force Detection in Wheel-Legged Robots by Chao Huang, Meng Hong, Yaodong Wang, Hui Chai, Zhuo Hu, Zheng Xiao, Sijia Guan, Min Guo

“…To address this challenge, this study proposes a foot–ground contact state detection technique and optimization method based on multi-sensor fusion and intelligent modeling for wheel-legged robots. …”
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Hybrid Optimization Method for Social Internet of Things Service Provision Based on Community Detection by Bahar Allakaram Tawfeeq, Amir Masoud Rahmani, Abbas Koochari, Nima Jafari Navimipour

“…Addressing these challenges requires efficient optimization methods. Traditional optimization algorithms have strengths and weaknesses. …”
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Abnormal traffic detection method based on LSTM and improved residual neural network optimization by Wengang MA, Yadong ZHANG, Jin GUO

“…Problems such as a difficulty in feature selection and poor generalization ability were prone to occur when traditional method was exploited to detect abnormal network traffic.Therefore, an abnormal traffic detection method based on the long short term memory network (LSTM) and improved residual neural network optimization was proposed.Firstly, the features and attributes of network traffic were analyzed, and the variability of the feature values was reduced by preprocessing of network traffic.Then, a three-layer stacked LSTM network was designed to extract network traffic features of different depths.Moreover, the problem of weak adaptability of feature extraction was solved.Finally, an improved residual neural network with skipping connecting line was designed to optimize the LSTM.The defects of deep neural network such as overfitting and gradient vanishing were optimized.The accuracy of abnormal traffic detection was improved.Experimental results show that the proposed method has higher training accuracy and better visibility of data processing.The classification accuracy rates under two classifications and multiple classifications are 92.3% and 89.3%.It has the lowest false positive rate when the parameters such as precision rate and recall rate are optimal.Moreover, it has strong robustness when the sample is destroyed.Furthermore, better generalization ability can be achieved.…”
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Arrhythmia detection with transfer learning architecture integrating the developed optimization algorithm and regularization method by Fatma Akalın, Pınar Dervişoğlu Çavdaroğlu, Mehmet Fatih Orhan

Subjects: “…Arrhythmia detection…”
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A Malware Detection Method Based on Genetic Algorithm Optimized CNN-SENet Network by Zheng Yang, Hua Zhu, Zhao Li, Gang Wang, Meng Su

“…To this end, this paper proposes a malware detection method based on genetic algorithm optimization of the CNN-SENet network, which firstly introduces the SENet attention mechanism into the convolutional neural network to enhance the spatial feature extraction capability of the model; then, the application programming interface (API) sequences corresponding to different software behaviors are processed by segmentation and de-duplication, which in turn leads to the sequence feature extraction through the CNN-SENet model; finally, genetic algorithm is used to optimize the hyperparameters of CNN-SENet network to reduce the computational overhead of CNN and to achieve the recognition and classification of different malware at the output layer. …”
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Enhancing Drone Detection via Transformer Neural Network and Positive–Negative Momentum Optimizers by Pavel Lyakhov, Denis Butusov, Vadim Pismennyy, Ruslan Abdulkadirov, Nikolay Nagornov, Valerii Ostrovskii, Diana Kalita

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Fuzzy clustering method based on genetic algorithm in intrusion detection study by HUANG Min-ming LIN Bo-gang

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Verifying hyperparameter sensitivities of optimal filter design methods for fault signature enhancement by Schmidt Stephan, Wilke Daniel N., Heyns Philippus Stephan, Gryllias Konstantinos C.

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A novel deep learning model based on YOLOv5 optimal method for coal gangue image recognition by Tongkai Gu, Haiyan Zhao, Yasheng Chang, Sitong Yan, Feihan Cao, Wei Liu

“…You Only Look Once version 5 (YOLOv5), with its rapid inference speed and high accuracy, offers a suitable solution for real-time coal gangue detection. This research investigates the application of YOLOv5 for coal gangue image recognition, involving data preprocessing, model training, and optimization. …”
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BG-YOLO: A Bidirectional-Guided Method for Underwater Object Detection by Ruicheng Cao, Ruiteng Zhang, Xinyue Yan, Jian Zhang

“…Degraded underwater images decrease the accuracy of underwater object detection. Existing research uses image enhancement methods to improve the visual quality of images, which may not be beneficial in underwater image detection and lead to serious degradation in detector performance. …”
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Optimizing DNA extraction methods for enhanced detection of pathogenic Leptospira spp. in cultures using PCR by Kiki Aprilia, Arif Mulyanto, Kurnia Ritma Dhanti, Korri El Khobar, Farida Dwi Handayani

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Optimal intrusion detection for imbalanced data using Bagging method with deep neural network optimized by flower pollination algorithm by Hussein Ridha Sayegh, Wang Dong, Bahaa Hussein Taher, Muhanad Mohammed Kadum, Ali Mansour Al-madani

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Optimal fault detection from seismic data using intelligent techniques: A comprehensive review of methods by Bhaktishree Nayak, Pallavi Nayak

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Application of an Optimized HPLC Method for the Detection of Various Phenolic Compounds in Apples from Lithuanian Cultivars by Mindaugas Liaudanskas, Pranas Viškelis, Valdas Jakštas, Raimondas Raudonis, Darius Kviklys, Arvydas Milašius, Valdimaras Janulis

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Enhancing Mycotoxin Detection in Table Olives: The Role of Enzyme-Linked Immunosorbent Assay and Method Optimization by Alessandro Cammerata, Viviana Del Frate, Tiziana Monforte, Antonio Scarfone, Elio Romano

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A Single-Stage Photovoltaic Module Defect Detection Method Based on Optimized YOLOv8 by Yihong Gao, Chengxin Pang, Xinhua Zeng, Pengyi Jiang

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A Rapid Sand Gradation Detection Method Based on Dual-Camera Fusion by Shihao Zhang, Yang Zhang, Song Sun, Xinghai Yuan, Haoxuan Sun, Heng Wang, Yi Yuan, Dan Luo, Chuanyun Xu

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Wind Turbine Blade Fault Detection Method Based on TROA-SVM by Zhuo Lei, Haijun Lin, Xudong Tang, Yong Xiong, He Wen

“…This method integrates the Tyrannosaurus Optimization Algorithm (TROA) with a support vector machine (SVM), aiming to enhance the accuracy and reliability of fault detection. …”
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