An Improved ARIMA-Based Traffic Anomaly Detection Algorithm for Wireless Sensor Networks by Qin Yu, Lyu Jibin, Lirui Jiang

“…Specifically, we improve the traditional time series ARIMA model to make traffic prediction and judge the traffic anomaly in a WSN. Simulated and real WSN traffic data gathered from University of North Carolina are used to carry out simulations on Matlab. …”
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Risk Assessment of the Rockburst Intensity in a Hydraulic Tunnel Using an Intuitionistic Fuzzy Sets-TOPSIS Model by Xin-Bao Gu, Qi-Hong Wu, Ying Ma

“…In total, it can provide a new route for the intensity prediction of rockburst in the future.…”
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Simulation and Modeling of Flow in a Gas Compressor by Anna Avramenko, Alexey Frolov, Jari Hämäläinen

“…The numerical simulation method in this paper can be used to predict compressor performance.…”
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Dynamic Parameter Identification And Control of Legged Robots’ Legs Considering Joint Friction Characteristics by Xiao Haoyang, Qian Letian, Luo Xin

“…Experiments on a heavy-duty quadruped robot indicate that the prediction error of joint torques utilizing the proposed method is reduced by about 40%, and the trajectory tracking accuracy is improved by more than 60%, comparing to those obtained by the existing identification and control method based on linear friction model.…”
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Automatic Capture Processing Method of Basketball Shooting Trajectory Based on Background Elimination Technology by Hongyan Fan, Youhong Hu, Jianfeng Zhang

“…The analysis and prediction of the shooting trajectory can be used to partially correct the shooting. …”
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Machine Learning-Based Scrap Steel Price Forecasting for the Northeast Chinese Market by Bingzi Jin, Xiaojie Xu

“…Throughout history, governments and investors have relied on predictions of prices for a broad spectrum of commodities. …”
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Space-time division cluster DoA estimation algorithm based on UWA spread spectrum signal by Feng ZHOU, Baosheng ZHANG, Wenbo ZHANG

“…To solve the problems of poor stability, low resolution, and performance degradation under low signal-to-noise ratio (SNR) of the direction of arrival (DoA) estimation, a space-time division cluster (STDC) DoA estimation algorithm was proposed for under water acoustic (UWA) spread spectrum signal.The idea of the time-frequency two-dimensional search was used to combine the conventional beamforming with the spread spectrum sequence, set the angle interval to search the incidence angle and the arrival delay of the spread-spectrum signal, and increased the spatial spectrum to the delay angle spectrum, which kept the high resolution.STDC-DoA estimation can be anti-interference and stable operation under low SNR by using the characteristics of spread spectrum sequence.Finally, through simulation and pool experiment, it was proved that compared with the traditional DoA estimation algorithm, the proposed algorithm has better performance in anti-interference, resolution, and anti-noise.Meanwhile, the proposed algorithm does not need signal source number estimation and angle prediction and has more robust performance.…”
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Evaluation of the Wind Energy Potential in the Coastal Environment of Two Enclosed Seas by Florin Onea, Alina Raileanu, Eugen Rusu

“…The work presents a comprehensive picture of the wind energy potential in the coastal environment of the Black and the Caspian Seas. 10-year of data coming from the US National Centers for Environmental Prediction was considered as the main source. This dataset was subsequently compared with both in situ and remotely sensed measurements. …”
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Energy-efficient chain-based data gathering applied to communicating concrete by Hang Wan, Michael David, William Derigent

“…Experimental results show the mean prediction error of our models is 5%. Realizing aggregation at nodes significantly reduces energy consumption and avoids hot-spot problem with homogeneous consumptions along the chain. …”
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Quality Classification of Lithium Battery in Microgrid Networks Based on Smooth Localized Complex Exponential Model by Zhelin Huang, Fangfang Yang

“…Accurate prediction of battery quality using early-cycle data is critical for battery, especially lithium battery in microgrid networks. …”
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Recognizing Cow Muzzle Patterns using the Convolution Neural Network (CNN) Algorithm by Sulthon Zamroni, Giri Wahyu Wiriasto, Bulkis Kanata

“…This research aims to develop a cattle muzzle identification system using convolutional neural networks method with Alexnet architecture and to identify the factors that can decrease the accuracy of prediction results. The results of this research can help cattle farmers manage their livestock data more effectively, as traditional identification methods can cause discomfort and stress to the cattle. …”
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Diffusion-limited tumour growth: Simulations and analysis by Philip Gerlee, Alexander R. A. Anderson

“…Comparison between the prediction of the stability analysis and the results from the simulations shows good agreement between theory and simulation.…”
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Sustainability models in Zone 3 manufacturing SMEs by Karla Morales, Pamela de Los Ángeles Sánchez Rosero, Christian Alberto López Valencia, Freddy Marco Armijos Arcos

“…Observation sheets were used to classify the information in the financial statements and allow understanding of their financial situation by applying the solvency prediction models, Z-Altman, Springate, Fulmer, and CA-Score. …”
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Experimental Studies on the Changes in Resistivity and Its Anisotropy Using Electrical Resistivity Tomography by Tao Zhu, Jian-Guo Zhou, Jin-Qi Hao

“…Our results show that with increasing pressure, resistivity and the decreased (D region) and increased (I region) resistivity regions have complex behaviors, but when pressure is higher than a certain value, the average resistivity decrease and the area of D region expand gradually in all time with the increase of pressure, which may be significant to the monitoring and prediction of earthquake, volcanic activities, and large-scale geologic motions. …”
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Modern Endoscopic Imaging in Diagnosis and Surveillance of Inflammatory Bowel Disease Patients by Gheorghe Hundorfean, Stephen P. Pereira, John G. Karstensen, Peter Vilmann, Adrian Saftoiu

“…Additionally, we discuss future directions and techniques as candidates for a superior inflammation imaging in the diagnosis and prediction of therapeutic response.…”
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A New Conformable Fractional-Order Time-Delay Grey Bernoulli Model with the Arithmetic Optimization Algorithm and Its Application in Rural Regional Economy by Ran Wang, Hui Liu, Qinwen Yang, Hongmei Du

“…Compared with the previous grey prediction models, the CFTDNGBM (1, 1) model with a conformable fractional-order accumulation operation (CFAO), time-delay factor, and Bernoulli parameter has stronger compatibility in structure. …”
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Development and Prospect of Water Quality Monitoring Technology Driven by Data-model Coupling by ZHU Lijie, HE Kai, HUANG Sheng, YIN Qidong, DAI Chao

“…In terms of water quality analysis and prediction, artificial intelligence techniques, such as machine learning and expert systems, have played a significant role. …”
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Yumuşak Güç Kavramı Çerçevesinde Avrasya Ekonomik Birliği ve Kuşak-Yol İnisiyatifinin Değerlendirilmesi by Göktürk TÜYSÜZOĞLU

“…However, the fact that both initiatives have generally targeted the same geography also leads to a prediction that China and Russia, which co-exist in the context of demand for systemic change in the current conjuncture, may lead to a long-term competitive conflic…”
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Dynamic Behavior of Self-Piercing Riveted and Mechanical Clinched Joints of Dissimilar Materials: An Experimental Comparative Investigation by Yulong Ge, Yong Xia

“…The influence of the strain-rate-dependent mechanical behavior of the substrates on the joints is examined; this can help improve prediction of the energy absorption of the joints under impact loading. …”
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Classification of reduction invariants with improved backpropagation by S. M. Shamsuddin, M. Darus, M. N. Sulaiman

“…On the other hand, backpropagation network has been used extensively in classification problems such as XOR problems, share prices prediction, and pattern recognition. This paper proposes an improved error signal of backpropagation network for classification of the reduction invariants using principal component analysis, for extracting the bulk of the useful information present in moment invariants of handwritten digits, leaving the redundant information behind. …”
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