Lung cancer Prediction and Classification based on Correlation Selection method Using Machine Learning Techniques by Dakhaz Mustafa Abdullah, Adnan Mohsin Abdulazeez, Amira Bibo Sallow

“…This paper endeavors to inspect accuracy ratio of three classifiers which is Support Vector Machine (SVM), K-Nearest Neighbor (KNN)and, Convolutional Neural Network (CNN) that classify lung cancer in early stage so that many lives can be saving. …”
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Effective Inertial Hand Gesture Recognition Using Particle Filtering Based Trajectory Matching by Zuocai Wang, Bin Chen, Jin Wu

“…After smoothing, the trajectory is then converted to low-definition images which are further sent to a backpropagation neural network (BP-NN) based recognizer for matching. …”
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A Cloud API Personalized Recommendation Method Based on Multiple Attribute Features and Mashup Requirement Attention by Limin Shen, Yuying Wang, Chengyu Li, Zhen Chen

“…To fully leverage information from intermediate nodes in the metapaths and emphasize the significance of different instances, we employ a translational distance model and graph neural network techniques to aggregate cloud API feature information. …”
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6G knowledge system construction: academic knowledge mining and on-demand application for full domains and omni scenarios by Zifan SHA, Nan CHENG, Yilong HUI, Wenwei YUE, Yuchuan FU, Ruijin SUN

“…At present, the concepts related to 6G have not been unified, and there is an urgent need for consistent cognition and definition.Academics and industries lack a clear understanding of the overall development of 6G and the research progress in related fields.Therefore, the 6G knowledge base and knowledge system was constructed.Firstly, the existing 6G academic documents were automatically screened and stored in a structured way.Secondly, a 6G knowledge base was constructed on the basis of labeling and standardizing text data.In addition, a comprehensive statistical analysis was conducted across all domains of 6G based on the knowledge base and the technologies such as natural language processing, deep neural network and latent tree model were used to realize the extraction and generation of 6G knowledge.Finally, on the basis of large-scale model training, the on-demand knowledge application was realized for diversified service requirements.…”
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Annual Energy Consumption Forecasting Based on PSOCA-GRNN Model by Huiru Zhao, Sen Guo

“…The generalized regression neural network (GRNN) model was employed to forecast the annual energy consumption due to its good ability of dealing with the nonlinear problems. …”
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A distributed strategy for the multi-target rescue using a UAV swarm under communication constraints by Hanqing YU, Yan LIN, Linqiong JIA, Qiang LI, Yijin Zhang

“…The current designs of the cooperative decision-making of an unmanned aerial vehicle (UAV) swarm usually adopt unreasonable assumptions on the communication ability between UAVs.Focusing on a multi-target rescue problem of a UAV swarm under constraints of energy, load and path, the limitation on the information sharing due to the communication constraints and the flight path of UAVs were taken into account.Firstly, the problem was formulated as a partially observable Markov decision process (POMDP).Then, a recurrent neural network was used to propose a deep-reinforcement-learning-based distributed rescue strategy, which is able to adapt to the changeable communication topology.Simulation results show that the proposed strategy outperforms other strategies under communication constraints, and further show that a careful joint setting of the size and communication ability of a UAV swarm is needed to achieve the best compromise between the UAV swarm rescue performance and the cost.…”
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Interface-engineered non-volatile visible-blind photodetector for in-sensor computing by Ge Li, Donggang Xie, Qinghua Zhang, Mingzhen Zhang, Zhuohui Liu, Zheng Wang, Jiahui Xie, Erjia Guo, Meng He, Can Wang, Lin Gu, Guozhen Yang, Kuijuan Jin, Chen Ge

“…A photodetector array operated as a single-layer neural network was constructed, in which edge detection and pattern recognition were realized without the need for external memory and computing units. …”
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Neuron-Adaptive PID Based Speed Control of SCSG Wind Turbine System by Shan Zuo, Yongduan Song, Lei Wang, Zheng Zhou

“…A simple yet effective single neuron-adaptive PID control scheme with Delta learning mechanism is proposed for the speed control of SCSG based wind power system, in which the RBF neural network (NN) is employed to estimate the uncertain but continuous functions. …”
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FSE-RBFNN-Based AILC of Finite Time Complete Tracking for a Class of Time-Varying NPNL Systems with Initial State Errors by Chunli Zhang, Lei Yan, Yangjie Gao

“…Addressing the difficulty of nonlinear parameterization terms in system models, a new function approximator (FSE-RBFNN) which is combined with radial basis function neural network (RBFNN) and Fourier series expansion (FSE) is introduced to model each time-varying nonlinear parameterization function. …”
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Real-Time Prediction of the Trend of Ground Motion Intensity Based on Deep Learning by Tao Liu, Zhijun Dai

“…According to the different sampling frequencies, the neural network is constructed by several subnetworks, and the output of each subnetwork is combined into one. …”
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Distributed Adaptive Coordinated Control of Multiple Euler–Lagrange Systems considering Output Constraints and Time Delays by Hongde Qin, Xiaojia Li, Yanchao Sun

“…In order to handle uncertain problems, the neural network technique is adopted to estimate the unknown dynamics. …”
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Hybrid Optimal Kinematic Parameter Identification for an Industrial Robot Based on BPNN-PSO by Guanbin Gao, Fei Liu, Hongjun San, Xing Wu, Wen Wang

“…A novel hybrid algorithm that employs BP neural network (BPNN) and particle swarm optimization (PSO) algorithm is proposed for the kinematic parameter identification of industrial robots with an enhanced convergence response. …”
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Simulated Annealing Based Hybrid Forecast for Improving Daily Municipal Solid Waste Generation Prediction by Jingwei Song, Jiaying He, Menghua Zhu, Debao Tan, Yu Zhang, Song Ye, Dingtao Shen, Pengfei Zou

“…A simulated annealing (SA) based variable weighted forecast model is proposed to combine and weigh local chaotic model, artificial neural network (ANN), and partial least square support vector machine (PLS-SVM) to build a more accurate forecast model. …”
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Optimization of cyber security through the implementation of AI technologies by Nawaf Liqaa, Bentotahewa Vibhushinie

“…The Metaheuristic algorithms are stimulated by the human brain, so implementing Artificial Intelligence (AI) that assists the Neural Network to mimic the behaviour of the human brain is important to predict significant outcomes. …”
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A High-Efficiency Charge-Domain Compute-in-Memory 1F1C Macro Using 2-bit FeFET Cells for DNN Processing by Nellie Laleni, Franz Muller, Gonzalo Cunarro, Thomas Kampfe, Taekwang Jang

“…The macro achieves 111.6 TOPS/W, highlighting its energy efficiency, and demonstrates robust performance on the CIFAR-10 dataset, achieving 89% accuracy with a VGG-8 neural network. These findings underscore the potential of charge-domain, multilevel NVM cells in pushing the boundaries of artificial intelligence (AI) acceleration and energy-efficient computing.…”
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Identification of Civil Infrastructure Damage Using Ensemble Transfer Learning Model by A. Shamila Ebenezer, S. Deepa Kanmani, V. Sheela, K. Ramalakshmi, V. Chandran, M. G. Sumithra, B. Elakkiya, Bharani Murugesan

“…The convolutional neural network has become a standard tool for organizing and recognizing images. …”
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A lightweight power quality disturbance recognition model based on CNN and Transformer by ZHANG Bide, QIU Jie, LOU Guangxin, ZHOU Can, LUO Qingqing, LI Tianqian

“…A lightweight power quality disturbances (PQDs) recognition model that integrates convolutional neural network (CNN) and Transformer (CaT) is proposed to address the high number of parameters and computational complexity in existing deep learning-based models. …”
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Application research on the time–frequency analysis method in the quality detection of ultrasonic wire bonding by Wuwei Feng, Xin Chen, Cuizhu Wang, Yuzhou Shi

“…Finally, an artificial neural network was built to recognize and detect the quality of ultrasonic wire bonding. …”
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An SDP Characteristic Information Fusion-Based CNN Vibration Fault Diagnosis Method by Xiaoxun Zhu, Jianhong Zhao, Dongnan Hou, Zhonghe Han

“…This study proposes a symmetrized dot pattern (SDP) characteristic information fusion-based convolutional neural network (CNN) fault diagnosis method to resolve issues of high complexity, nonlinearity, and instability in original rotor vibration signals. …”
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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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