Study of Register Value Branch Predictor Based on CNN by Yingjie Tang, Zhangjin Chen, Wuyi Fang

“…In particular, the data-related branches are a difficult problem to be handled by the current predictors. In this paper, we continue to study Zangeneh’s BranchNet CNN neural network branch predictor to explore the solution. …”
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Measurement of intelligent computing via Levenberg Marquardt algorithm (LMA) for accurate prediction of fluid forces in a transient non-Newtonian thermal flow by Atif Asghar, Rashid Mahmood, Afraz Hussain Majeed, Ahmed S. Hendy, Mohamed R. Ali

“…Fast second-order LMA, a top-tier approach, was used to train the network. Both the Mean Square Error (MSE) and the coefficient of determination (R) provide statistical evidence that the ANN projected values for the drag and lift coefficients and average Nusselt number obtained from the finite element analysis are accurate. …”
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A Multimodal Machine Learning Model in Pneumonia Patients Hospital Length of Stay Prediction by Anna Annunziata, Salvatore Cappabianca, Salvatore Capuozzo, Nicola Coppola, Camilla Di Somma, Ludovico Docimo, Giuseppe Fiorentino, Michela Gravina, Lidia Marassi, Stefano Marrone, Domenico Parmeggiani, Giorgio Emanuele Polistina, Alfonso Reginelli, Caterina Sagnelli, Carlo Sansone

“…While many existing models simplify the LOS prediction problem to a classification task, predicting broad ranges of hospital days, an exact day-based regression model is often crucial for precise planning. …”
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Stable Simulation of the Community Atmosphere Model Using Machine‐Learning Physical Parameterization Trained With Experience Replay by Jianda Chen, Minghua Zhang, Tao Zhang, Wuyin Lin, Wei Xue

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SPCB-Net: A Multi-Scale Skin Cancer Image Identification Network Using Self-Interactive Attention Pyramid and Cross-Layer Bilinear-Trilinear Pooling by Xin Qian, Tengfei Weng, Qi Han, Chen Wu, Hongxiang Xu, Mingyang Hou, Zicheng Qiu, Baoping Zhou, Xianqiang Gao

“…Deep convolutional neural networks have made some progress in skin lesion classification and cancer diagnosis, but there are still some problems to be solved, such as the challenge of small inter-class feature differences and large intra-class feature differences, which might limit the classification performance of the model as high-level and low-level features are not properly utilized. …”
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Energy Efficiency of Using Hybrid Heating Points in Conditions of Integration of Electrical and Thermal Networks of Urban Neighborhoods. Part 1. Justification of the Feasibility of... by A. V. Sednin, M. I. Pozdnyakova

“…If during the new construction the power of the electrical network may vary depending on the selected option, then during the modernization of the heat supply system, the problem is solved if there is a limitation on the available electrical power. …”
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Hierarchical clustering methods in a task to find abnormal observations based on groups with broken symmetry by A. N. Kislyakov, S. V. Polyakov

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Landslide Forecasting Model Based on PCA and Improved CS-RBF by WANG Lianxia, LI Limin, FANG Zihao, REN Ruibin, FU Zhentao, CUI Chengtao

“…Taking the landslide monitoring points in Shanyang County, Shaanxi Province as an example, this study proposes a landslide probability forecasting model based on principal component analysis (PCA) and cuckoo search (CS) optimized radial basis function (RBF) neural network. Firstly, the main influencing factors of landslide disasters in the area are determined, and the PCA algorithm is used to reduce the dimensionality of landslide influencing factors to avoid the problem of model redundancy caused by excessively large data dimensions. …”
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Botnet detection in internet of things using stacked ensemble learning model by Mudasir Ali, Muhammad Faheem Mushtaq, Urooj Akram, Daniel Gavilanes Aray, Manuel Masias Vergara, Hanen Karamti, Imran Ashraf

“…Despite existing approaches for cyber attack detection, botnets prove to be a particularly difficult problem that calls for more advanced detection methods. …”
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Malware detection approach based on improved SOINN by Bin ZHANG, Lixun LI, Shuqin DONG

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Training RBF NN Using Sine-Cosine Algorithm for Sonar Target Classification by Yixuan WANG, LiPing YUAN, Mohammad KHISHE, Alaveh MORIDI, Fallah MOHAMMADZADE

“…Radial basis function neural networks (RBF NNs) are one of the most useful tools in the classification of the sonar targets. …”
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Estimating pedestrian traffic with Bluetooth sensor technology by Avital Angel, Achituv Cohen, Sagi Dalyot, Pnina Plaut

“…This study aims to accurately detect pedestrians using a network of 65 Bluetooth detectors located in Tel-Aviv, Israel, which record on average over 60,000 unique daily Bluetooth Media-Access-Control addresses. …”
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Improved CNN-GRU algorithm application in enterprise legal consultation system by Xuejie Zhao

“…The study proposes an improved neural network that combines deformable convolution and gated recurrent units for convolution problems. …”
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Chaotic moving video quality enhancement based on deep in-loop filtering by Tong Tang, Yi Yang, Dapeng Wu, Ruyan Wang, Zhidu Li

“…Then, a deep in-loop filtering method is proposed based on the blur-aware network to replace the VVC in-loop filter. Finally, experimental results show that the proposed method could averagely save 8.3% of bit consumption at similar subjective quality. …”
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Path planning algorithm for WCE with joint energy replenishment and data collection based on multi-objective optimization by Zhenchun WEI, Renhao SUN, Zengwei LYU, Jianghong HAN, Lei SHI, Junyi XU

“…Considering limited energy of the wireless charging equipment (WCE) in wireless rechargeable sensor network,an energy replenishment strategy and a data collection strategy are designed.On the basis of these,a path planning model for WCE with functions of joint energy replenishment and data collection based on multi-objective optimization is constructed with two optimization objectives,maximizing the total energy utility of WCE and minimizing the average delay of data transmission of all the sensor nodes in the network.To deal with it,a multi-objective ant colony optimization algorithm based on elitist strategy was proposed,where the state transition strategy and the pheromone updating strategy were improved.Then,the Pareto set was obtained in terms of this multi-objective optimization problem.The parameter setting of ant colony algorithm’s effects on the proposed algorithm were analyzed under 20 sensor nodes.50 groups of contrastive experiments show that the average number of energy utilization obtained by ES-MOAC algorithm is 4.53% higher than that of NSGA-II algorithm.The average number of average delay of all node data transmission obtained by ES-MOAC algorithm is 5.12% lower than that of NSGA-II algorithm.…”
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Optimizing Remote Sensing Image Retrieval Through a Hybrid Methodology by Sujata Alegavi, Raghvendra Sedamkar

“…Semantic-based image retrieval remains an open problem due to limitations in current artificial intelligence techniques. …”
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Wakeup strategy based on multi-objective optimization for fixed relay nodes by Xue-bin MA, Ai-li LI, Xiao-juan ZHANG

“…In order to deal with the “tidal effect” when people move in the city and solve the problem of high energy consumption of fixed relay nodes in opportunistic networks,a wakeup strategy of multi-objective optimization was proposed,which made use of the message forward ability and energy consumption of fixed relay nodes.This strategy used energy efficiency as the indicator to make the nodes awake,and deployed a network revenue-energy consumption model to resolve the contradiction between energy consumption and message forward ability.As the selection problem of awake relay nodes was a NP-hard problem,genetic algorithm was used to select proper fixed relay nodes to keep awake.In this process,selection operator was improved to make the algorithm converge to solution space quickly.Experiments show that the proposed wakeup strategy can guarantee the successful rate of message transmission and improve the average message forwarding capabilities of fixed relay nodes by consuming a unit energy.…”
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An edge server placement based on graph clustering in mobile edge computing by Shanshan Zhang, Jiong Yu, Mingjian Hu

“…The model mainly consists of a two-layer graph convolutional network (GCN) component and a differentiable version of K-means clustering component, which transforms the server placement problem into an end-to-end learning optimization problem on a graph. …”
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MATHEMATICAL MODEL OF THE LOAD BALANCING SYSTEM OF DPC SERVER CLUSTERS UNDER FRACTAL LOAD CONDITIONS by V. P. Mochalov, N. Yu. Bratchenko, I. S. Palkanov, E. V. Aliev

“…The characteristics of the average queue length, average delay, and packet loss probability were used as the main quality indicators. …”
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A Novel Mixed-Precision Quantization Approach for CNNs by Dan Wu, Yanzhi Wang, Yuqi Fei, Guowang Gao

“…In this paper, we propose an efficient mixed-precision search method that tackles this problem. It first utilizes the average approximation trace of the Hessian matrix to determine the sensitivity of each convolutional layer to quantization. …”
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