Social media user geolocalization based on multiple mention relationships by Yaqiong QIAO, Xiangyang LUO, Jiangtao MA, Chenliang LI, Meng ZHANG, Ruixiang LI

“…Aiming at the problem that the existing joint user geolocalization methods based on social media text and social relationships do not sufficiently mine the location correlation between heterogeneous data in social media, a social media user geolocalization method based on multiple mention relationships was proposed.First, a heterogeneous network was constructed by comprehensively considering the mention relationship between users, the user's mention relationship with location indicative words, and the user's mention relationship with geographic nouns.Then, a network simplification strategy was proposed to construct a user-location heterogeneous network that connects users live nearby more closely based on the common mention relationship.After that, a biased random walk algorithm was proposed for the graph node sampling to fully explore the network structure and alleviate the sparsity problem of known locations.Finally, a neural network classifier based on a multilayer perceptron was used to infer the user's location.Experimental results on three representative Twitter data sets of GEOTEXT, TW-US and TW-WORLD show that the proposed method can significantly improve the user geolocalization accuracy.…”
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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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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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Research of the Trajectory Tracking Method for Four-wheeled Omnidirectional Mobile Robot based on the Adaptive Sliding Mode Control by Xing Yanrong, Qin Jiawei, Su Caiyun

“…At the same time a parameter adaptive control algorithm is proposed in order to achieve the online estimation of the robot dynamics parameters,and real- time switch gain adjustment of trajectory tracking controller is achieved by using RBF neural network as to reduce the chattering of the system. …”
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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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The Network Global Optimal Mapping Approach Utilizing a Discrete Firefly Optimization Algorithm by He Jia, Li Xiaomei

“…Then, a resolution of the multi-layered neural network is proposed. A resolution has been saved at all levels of the structure. …”
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Risk Assessment of Government Debt Based on Machine Learning Algorithm by Dan Chen

“…According to forming the performance of local government debt risk and its internal and external influencing factors, this study applies the analytic hierarchy process, entropy method, and BP neural network method to construct the local government risk assessment index system, which includes the primary and secondary indexes including the explicit debt risk, the contingent implicit debt risk, and the financial and economic operation risk. …”
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A Design Space Exploration Framework for ANN-Based Fault Detection in Hardware Systems by Andreas G. Savva, Theocharis Theocharides, Chrysostomos Nicopoulos

“…This work presents a design exploration framework for developing a high level Artificial Neural Network (ANN) for fault detection in hardware systems. …”
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A Neural-Wavelet Technique for Damage Identification in the ASCE Benchmark Structure Using Phase II Experimental Data by Mahmoud M. Reda Taha

“…We describe a robust damage detection method that is based on using artificial neural network (ANN) to compute the wavelet energy of acceleration signals acquired from the structure. …”
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Temperature and Humidity Prediction Based on Machine Learning by Xiong Yanqi

“…Support Vector Machine(SVM), Neural Network(NN), and Random Forest(RF). to analyze their accuracy in predicting temperature and humidity. …”
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Rancang Bangun Aplikasi Berbasis Android untuk Perbaikan Kualitas Citra Tanaman Atas Perbedaan Spesifikasi Kamera Smartphone pada Prediksi Kandungan Pigmen Fotosintesis Secara Real... by Felix Adrian Tjokro Atmodjo, Kestrilia Rega Prilianti, Hendry Setiawan

“…An Android based application called Fuzzy Piction could predict the content of those pigments nondestructively using the FP3Net, a Convolutional Neural Network (CNN) model. This application predicts the pigment content in plant leaf by its digital images. …”
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Teknologi Irigasi Cerdas pada Sistem Irigasi Drip dengan Algoritma Ant Colony Optimization by Abdul Haris, Nabilla Anggraini, Hengki Sikumbang

“…Banyak peneliti yang telah melakukan kajian dan inovasi di bidang ini untuk menghasilkan irigasi yang baik dan optimal, antara lain dengan mengimplementasikan gabungan Internet of Things (IoT) sebagai infrastruktur, Fuzzy Logic dan Artificial Neural Network (ANN) sebagai algoritma untuk menentukan waktu buka tutup dari Solenoid Valve dalam pengaturan distribusi air.  …”
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Whole examination AI estimation of fetal biometrics from 20-week ultrasound scans by Lorenzo Venturini, Samuel Budd, Alfonso Farruggia, Robert Wright, Jacqueline Matthew, Thomas G. Day, Bernhard Kainz, Reza Razavi, Jo V. Hajnal

“…In this paper, we introduce a paradigm shift that attains human-level performance in biometric measurement by aggregating automatically extracted biometrics from every frame across an entire scan, with no need for operator intervention. We use a neural network to classify each frame of an ultrasound video recording. …”
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CSO Intelligent Optimization of Drag Torque Parameters of Wet Brakes Based on the SSA-BP Approximate Model by Li Jie, Wang Shuai, Lan Hai, Wang Zhiyong

“…To solve the engineering problem of power loss in wet brakes under non-braking conditions, taking into consideration the influence of the lubricating oil in the clearance of friction pairs on the drag torque of the friction pair, making use of the strong nonlinear fitting ability of the sparrow-search-algorithm-back propagation (SSA-BP) neural network, and taking the no-load operating condition of wet brakes as the input variable and the drag torque as the output variable, an approximate model of wet brakes is established. …”
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Research on Fault Diagnosis Method Based on Improved CNN by Hu Hao, Feng Fuzhou, Zhu Junzhen, Zhou Xun, Jiang Pengcheng, Jiang Feng, Xue Jun, Li Yazhi, Sun Guanghui

“…To solve these problems, a fault diagnosis method based on an improved convolutional neural network (CNN) is proposed. Based on the traditional CNN model, a variety of convolution stride modes were added to extract features of different scales of signals and expand the feature dimension. …”
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THE BIONIC INTELLIGENT FAULT DIAGNOSIS BASED ON COMPREHENSIVE DIFFERENCES MINING FOR HYDRO TURBINE by CHEN XiaoYue, GE Dang, HUANG JiangPing, LIU Xiong, ZHANG XiaoYan

“…For the faults of hydropower unit with strong coupling and uncertainty,the traditional fault expression method based on the uniform feature vector is easy to submerge the effect of fault expression and limit the fault diagnosis accuracy and timeliness directly.Given this,we presented a bionic fault diagnosis method,which imitates the human brain thinking and proposes the concept of dependent feature vector（DFV）,which logical structure is described by feature selection tree and extracted by feature extraction tree.DFV deeply excavates the intricate relationship between faults by using its nested structure,and realizes the comprehensive mining of the quantity and quality differences between faults of hydroelectric units.It deeply reveals the intrinsic relationship between different faults and faults and features,effectively extracts the essential differences of different faults,and improves the validity of fault expression.Furthermore,the intelligent classification method is realized by combining DFV and probabilistic neural network,the experimental results show that the method can complete the fault diagnosis of hydropower units and achieve excellent diagnostic validity and timeliness.…”
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Advancing buffet onset prediction: a deep learning approach with enhanced interpretability for aerodynamic engineering by Jing Wang, Wei Liu, Hairun Xie, Miao Zhang

“…In this study, utilizing a comprehensive database of supercritical airfoils generated through numerical simulations, a convolutional neural network (CNN) model is firstly developed to perform buffet classification based on the flow fields. …”
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FAULT DIAGNOSIS METHOD OF AIRBORNE FUEL PUMP BASED ON CEEMD SHANNON ENTROPY AND GAPSO-SVM by BAO Jie, JING Bo, JIAO XiaoXuan, ZHANG QingYi, ZHANG Yu

“…Compared with BP neural network, SVM optimized by particle swarm optimization（PSO） and SVM optimized by genetic algorithm（GA）, the results showed that the model of SVM diagnosis optimized by GA has the advantages of fast training, high accuracy and short time-effect, and it has good engineering application value.…”
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Characterization of Short-Term Strength Properties of Fiber/Cement-Modified Slurry by Ping Jiang, Tianhao Mao, Na Li, Liang Jia, Fang Zhang, Wei Wang

“…A formula satisfying the accuracy requirement was obtained by fitting the stress-strain curves using the back propagation (BP) neural network algorithm. Five parameters, including peak strength, failure strain, initial elastic modulus, residual strength, and energy dissipation, were used to characterize the short-term strength properties of fiber/cement-modified slurry. …”
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Effect of Process Parameters on Short Fiber Orientation along the Melt Flow Direction in Water-Assisted Injection Molded Part by Haiying Zhou, Hesheng Liu, Qingsong Jiang, Tangqing Kuang, Zhixin Chen, Weiping Li

“…The effect of six process parameters, including filling time, melt temperature, mold temperature, delay time, water pressure, and water temperature, on the SFO along the melt flow direction were studied through orthogonal experimental design, range analysis, and variance analysis. An artificial neural network was used to establish the nonlinear agent model between the process parameters and A11 representing the fiber orientation in melt flow direction. …”
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