Tourism Growth Prediction Based on Deep Learning Approach by Xiaoling Ren, Yanyan Li, JuanJuan Zhao, Yan Qiang

“…The outcome of this study showed that the performance of the adopted deep learning framework was better than that of artificial neural network and support vector regression models. Practitioners can rely on the identified relevant features from the developed framework to understand the nature of the relationships between the predictive factors of tourist demand and the actual volume of tourist arrival.…”
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Gesture recognition based on flexible solar cells and ultrathin hydrogel film by Rucheng WU, Wenbo DING, Xiaomin XU, Linqi SONG, Weitao XU

“…Daily life involves various gestures, and combining these with smart wearable devices is crucial for improving quality of life.One effective solution to the challenges of gesture recognition and device energy consumption isutilizing the photoelectric conversion characteristics of solar energy-related devices.The data of five commonly used gestures were collected in the research of the combination of flexible solar cells and gesture recognition.Z-Score, low-pass filter, sliding window techniques for signal processing were applied, and successfully achieved 100% predicted accuracy using random forest, support vector machine and neural network algorithms even with small samples which showed that this method had significant advantages in the application of gesture recognition.…”
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STUDY OF LIGHTWEIGHT DESIGN ON GIRDER OF BRIDGE CRANE by TANG Hui, YU LanFeng, YAN Fei, ZHAO DengShan

“…In this paper,taking the bridge crane with 20t- 22. 5m as an example,utilization of ANSYS and multidisciplinary design optimization software Isight,based on the theory of Latin hypercube design,BP neural network,Hooke-Jeeves algorithm,presenting a better and faster optimization method for main girder of bridge crane. …”
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CONDITION ASSESSMENT OF THIN-WALLED ROBOT BEARING BASED ON MULITI-SENSOR DATA FUSION by LIU Yang, XIE TanCheng, XU YanWei, WANG Bing, LI BanHu

“…Finally, self organizing maps（SOM） neural network was used to integrate the characteristics information of AE and vibration signals. …”
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Application of big data technology in agricultural Internet of Things by Chunling Zhang, Zunfeng Liu

“…The Web Service technology is used to connect the Internet of Things with the neural network model to achieve data interoperability. …”
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PREDICTION OF CUTTING LOAD OF DRUM SHEARER BASED ON DEEP BELIEF NETWORK by MAO Jun, GUO Hao, CHEN HongYue

“…The test results show that the proposed method is suitable for predicting the load of the spiral drum of coal miner,which has strong characteristic extraction ability and better performance than BP neural network.…”
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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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Channel state information acquisition algorithm based on deep learning for IoT by Yong LIAO, Haimei YAO, Yuanxiao HUA

“…To solve the problem of high feedback overhead when the user sends channel state information (CSI) to the base station in massive multiple input multiple output (MIMO) based on Internet of things system,a CSI feedback network based on deep learning was proposed to feedback CSI.Firstly,the proposed network used convolutional neural network (CNN) to extract channel feature vectors and maxpooling to compress the data.Then the compressed CSI was decompressed by using full connection and CNN to restore the original channel.The simulation results show that compared with the existing CSI feedback methods,the CSI recovered by the proposed CSI feedback network is closer to the original channel,and the reconstruction quality is improved significantly.…”
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Adaptive Backstepping Tracking Control of Wheeled Mobile Manipulator With Output Constraints by Huzhenyu Zhang, Dmitry A. Yudin, Dmitry A. Makarov

“…Further, a radial basis function neural network is employed to compensate for dynamic uncertainties and external disturbances. …”
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À la recherche des réseaux intertextuels : défis de la recherche littéraire à grande échelle by Valentina Fedchenko, Dario Maria Nicolosi, Glenn Roe

“…From corpus and metadata cleaning to training a neural network for filtering ‘noisy’ passages, this article provides a pragmatic technical pipeline for similar projects working with massive collections of digitised text, highlighting both the promise and perils of conducting literary research at scale.…”
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BotCatcher:botnet detection system based on deep learning by Di WU, Binxing FANG, Xiang CUI, Qixu LIU

“…Machine learning technology has wide application in botnet detection.However,with the changes of the forms and command and control mechanisms of botnets,selecting features manually becomes increasingly difficult.To solve this problem,a botnet detection system called BotCatcher based on deep learning was proposed.It automatically extracted features from time and space dimension,and established classifier through multiple neural network constructions.BotCatcher does not depend on any prior knowledge which about the protocol and the topology,and works without manually selecting features.The experimental results show that the proposed model has good performance in botnet detection and has ability to accurately identify botnet traffic .…”
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Research on the Spatial Network Connection Characteristics and Influencing Factors of Chengdu–Chongqing Urban Agglomeration from the Perspective of Flow Space by Yangguang Hao, Zhongwei Shen, Jiexi Ma, Jiawei Li, Mengqian Yang

“…Based on the results of the SOM neural network machine learning model, the connectivity capabilities of cities within the CCUA are divided into five levels. …”
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A deep learning approach for predicting the antenna pointing error caused by transmission faults with simulation data by Lihui Chen, Song Xue, Peiyuan Lian, Qian Xu, Meng Wang, Congsi Wang

“…Finally, labeled fault data and antenna pointing errors have been put into the deep neural network model for training to obtain the prediction model for predicting antenna axis error. …”
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Multi-label text classification via secondary use of large clinical real-world data sets by Sai Pavan Kumar Veeranki, Akhila Abdulnazar, Diether Kramer, Markus Kreuzthaler, David Benjamin Lumenta

“…In comparison to the transformer-based architecture, we were levering the non-contextual model fastText, a convolutional neural network, a support vector machine and logistic regression for a comparative analysis of possible coding performance. …”
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An Intelligent Crow Search Optimization and Bi-GRU for Forest Fire Detection System Using Internet of Things by Syed Abdul Moeed, Bellam Surendra Babu, M. Sreevani, B. V. Devendra Rao, R. Raja Kumar and Gouse Baig Mohammed

“…To facilitate efficient detection at the outbreak of forest fires, a bi-directional gated recurrent neural network (Bi-GRU-NN) is needed. This neural network architecture is capable of processing sequential data from multiple directions, enhancing the system’s ability to predict the spread and intensity of fires. …”
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Design of low-carbon planning model for vehicle path based on adaptive multi-strategy ant colony optimization algorithm by Qi Guo, Rui Li, Changjiang Zheng, Gwanggil Jeon

“…Subsequently, a graph neural network (GNN) is utilized to optimize nodes and edges computationally. …”
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Drug Efficacy Recommendation System of Glioblastoma (GBM) Using Deep Learning by Sajid Naveed, Mujtaba Husnain, Ali Samad, Amna Ikram, Hina Afreen, Ghulam Gilanie, Najah Alsubaie

“…A panel of 47 genes associated with GBM was processed using two deep learning models: Artificial Neural Network (ANN) and Convolutional Neural Network (CNN). …”
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Generation of Variations on Theme Music Based on Impressions of Story Scenes Considering Human's Feeling of Music and Stories by Kenkichi Ishizuka, Takehisa Onisawa

“…Genetic algorithms (GAs) using modular neural network (MNN) models as fitness functions are applied to music generation in order to reflect user's feeling of music and stories. …”
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A Comparative Study of Cross-Device Finger Vein Recognition Using Classical and Deep Learning Approaches by Tuğçe Arıcan, Raymond Veldhuis, Luuk Spreeuwers, Loïc Bergeron, Christoph Busch, Ehsaneddin Jalilian, Christof Kauba, Simon Kirchgasser, Sébastien Marcel, Bernhard Prommegger, Kiran Raja, Raghavendra Ramachandra, Andreas Uhl

“…This study aims to fill this gap by introducing a cross-device finger vein dataset and evaluating the performance of finger vein recognition across devices using a classical method, a convolutional neural network, and our proposed patch-based convolutional auto-encoder (CAE). …”
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Dynamic hierarchy resource management for heterogeneous cognitive network by Juan WEN, Min SHENG, Yan ZHANG

“…A dynamic hierarchy resource management approach-DHRM based on intelligent prediction was proposed for heterogeneous cognitive network.In DHRM,according to different time scale,the method of wavelet neural network,wiener prediction and reinforcement learning were brought to get the variation of traffic d ion,the resource requirement of the handover calls,and the information of users’preferences,and available hierarchical resources of all networks were allocated flexibly.Multi-attribute decision making method,based on network status and user preference was used to make decision to dynamically assign network traffic flow to the most appropriate network.Simulation results show that,the system capacity is improved about 20% by DHRM compared with the other joint radio resource management algorithms.…”
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