Design of nonlinear rubber vibration isolators with low resonant frequency and high load bearing capacity by Xiaoqi Zhang, Xin Li, Fei Du, Fucai Hu, Li Wang, Yongsheng Yu

“…The rubber isolator static and dynamic behavior prediction models suitable for engineering applications are first established, where Yeoh model is adopted for rubber strong nonlinear feature prediction. …”
Get full text

Multifactor Stock Selection Strategy Based on Machine Learning: Evidence from China by Jieying Gao, Huan Guo, Xin Xu

“…The main findings are as follows: the support vector regression has the most stable successful rate for predicting, while ridge regression and linear regression have the most unstable successful rate with more extreme cases; algorithm of support vector regression fitting higher-degree polynomials in Chinese A-share market is optimized, compared with the traditional linear regression both in terms of stock return and retracement control; the results of support vector regression significantly outperforming the CSI 500 index prove further.…”
Get full text

End-Point Static Control of Basic Oxygen Furnace (BOF) Steelmaking Based on Wavelet Transform Weighted Twin Support Vector Regression by Chuang Gao, Minggang Shen, Xiaoping Liu, Lidong Wang, Maoxiang Chu

“…Finally, the results of proposed prediction models show that the prediction error bound with 0.005% in carbon content and 10°C in temperature can achieve a hit rate of 92% and 96%, respectively. …”
Get full text

Optimal transport reveals dynamic gene regulatory networks via gene velocity estimation. by Wenjun Zhao, Erica Larschan, Björn Sandstede, Ritambhara Singh

“…Our algorithm overcomes this limitation by estimating gene velocities using optimal transport. …”
Get full text

Automated Symbolic Upscaling: 2. Model Generation for Extended Applicability Regimes by Kyle Pietrzyk, Ilenia Battiato

“…This strategy extends the applicability of homogenized models with respect to classical homogenization theory, as demonstrated in Part 1 where upscaled models are rigorously derived in moderately reactive physical regimes. After encoding the algorithm into Symbolica, an automated upscaling framework, we upscale two reactive mass transport problems and numerically validate the resulting nonlinear homogenized models by showing the absolute error estimates predicted by homogenization theory are satisfied. …”
Get full text

Intelligent scheduling mechanism of time-sensitive network modal in polymorphic network by Sijin YANG, Lei ZHUANG, Yu SONG, Jiaxing WANG, Xinyu YANG

“…For the problems of uncertain forwarding scheduling and long solving time of time-sensitive network modal in polymorphic network, a joint routing and scheduling mechanism of time-sensitive network modal based on CSQF was proposed.Considering the requirement of bounded delay, network state and different routing mechanisms, a hybrid resource scheduling problem of joint cache queue and routing was formulated to optimize the resource usage of the entire network.Then, the traffic characteristics and cache queue utilization was used to predict the cache utilization of the next cycle, which was based on deep reinforcement learning.In addition, by using multi-queue CSQF forwarding scheduling mechanism and explicit routing algorithm based on cache utilization, an iterative scheduling algorithm was proposed to achieve deterministic forwarding and resource allocation.Simulation results show that the mechanism can effectively adjust the transmission scheduling of deterministic applications according to the resource usage of the network, and has better schedulability compared with other off-line scheduling mechanisms.…”
Get full text

A Voronoi-Based Location Privacy-Preserving Method for Continuous Query in LBS by Chunguang Ma, Changli Zhou, Songtao Yang

“…And then, a query algorithm is proposed without providing any user's actual location, replaced by continuous anchor sequence, to LBS provider. …”
Get full text

Intelligent scheduling mechanism of time-sensitive network modal in polymorphic network by Sijin YANG, Lei ZHUANG, Yu SONG, Jiaxing WANG, Xinyu YANG

“…For the problems of uncertain forwarding scheduling and long solving time of time-sensitive network modal in polymorphic network, a joint routing and scheduling mechanism of time-sensitive network modal based on CSQF was proposed.Considering the requirement of bounded delay, network state and different routing mechanisms, a hybrid resource scheduling problem of joint cache queue and routing was formulated to optimize the resource usage of the entire network.Then, the traffic characteristics and cache queue utilization was used to predict the cache utilization of the next cycle, which was based on deep reinforcement learning.In addition, by using multi-queue CSQF forwarding scheduling mechanism and explicit routing algorithm based on cache utilization, an iterative scheduling algorithm was proposed to achieve deterministic forwarding and resource allocation.Simulation results show that the mechanism can effectively adjust the transmission scheduling of deterministic applications according to the resource usage of the network, and has better schedulability compared with other off-line scheduling mechanisms.…”
Get full text

Extracting Pole Characteristics of Complex Radar Targets for the Aircraft in Resonance Region Using RMSPSO_ARMA by Sang Zhou, Huotao Gao, Fangyu Ren

“…The extraction algorithm of target characteristics resonance set at the high-frequency band plays a significant role in defense applications like early warning. …”
Get full text

Fingernail analysis management system using microscopy sensor and blockchain technology by Shih Hsiung Lee, Chu Sing Yang

“…The performance of each feature extraction algorithm was analyzed for the two classifiers and the deep neural network algorithm was used comparatively. …”
Get full text

Personalized Product Recommendation Model of Automatic Question Answering Robot Based on Deep Learning by Jie Peng, Jianhui Xu

“…Then, the bidirectional gated recurrent unit (Bi-GRU) is used to construct the score prediction matrix, and through the dynamic collaborative filtering algorithm to integrate the time characteristics of the user’s interest changes. …”
Get full text

A Statistical Analysis Based Probabilistic Routing for Resource-Constrained Delay Tolerant Networks by Jixing Xu, Jianbo Li, Shan Jiang, Chenqu Dai, Lei You

“…In this paper, we propose an improved probabilistic routing algorithm that fully takes into account message's time-to-live when predicting the delivery probability. …”
Get full text

Probabilistic Solar Proxy Forecasting With Neural Network Ensembles by Joshua D. Daniell, Piyush M. Mehta

“…Currently, the USAF contracts Space Environment Technologies (SET), which uses a linear algorithm to forecast F10.7cm. In this work, we introduce methods using neural network ensembles with multi‐layer perceptrons (MLPs) and long‐short term memory (LSTMs) to improve on the SET predictions. …”
Get full text

Assessment of Melon Fruit Nutritional Composition Using VIS/NIR/SWIR Spectroscopy Coupled with Chemometrics by Dimitrios S. Kasampalis, Pavlos Tsouvaltzis, Anastasios S. Siomos

“…Variable importance in projection (VIP) analysis confirmed that specific wavelengths between 680 and 720 nm, 900 and 1000 nm, 1400 and 1500 nm, and 1900 and 2000 nm were consistently critical in predicting the SSC, DM, and SSC/TA ratio. The highest VIP scores for SSC prediction were noted around 690 nm and 950 nm, while dry matter prediction was influenced most by wavelengths in the 1450 nm to 1950 nm range. …”
Get full text

Modeling Chaotic Behavior of Chittagong Stock Indices by Shipra Banik, Mohammed Anwer, A. F. M. Khodadad Khan

“…In this paper, a comparative study has been conducted to predict stock index values using soft computing models and time series model. …”
Get full text

Improving medical machine learning models with generative balancing for equity and excellence by Brandon Theodorou, Benjamin Danek, Venkat Tummala, Shivam Pankaj Kumar, Bradley Malin, Jimeng Sun

“…Abstract Applying machine learning to clinical outcome prediction is challenging due to imbalanced datasets and sensitive tasks that contain rare yet critical outcomes and where equitable treatment across diverse patient groups is essential. …”
Get full text

Multiclass Classification of Solar Flares in Imbalanced Data Using Ensemble Learning and Sampling Methods by Haodi Jiang, Ryoma Matsuura, Jason T. L. Wang

“…Furthermore, we develop an ensemble algorithm that uses nine classifiers as base learners and logistic regression as meta-learner. …”
Get full text

Research on gating alignment strategy for flow scheduling in satellite formation by XU Chuan, ZHANG Rufeng, HE Xiongwen, CUI Zhaojing, ZHAO Guofeng

“…Secondly, an online rolling gray scale prediction algorithm was designed to predict the delay of inter-node links, and based on the prediction results, the gated list deviation of neighboring nodes could be corrected dynamically to ensure the consistency of multi-node gated scheduling. …”
Get full text

Research on gating alignment strategy for flow scheduling in satellite formation by XU Chuan, ZHANG Rufeng, HE Xiongwen, CUI Zhaojing, ZHAO Guofeng

“…Secondly, an online rolling gray scale prediction algorithm was designed to predict the delay of inter-node links, and based on the prediction results, the gated list deviation of neighboring nodes could be corrected dynamically to ensure the consistency of multi-node gated scheduling. …”
Get full text

Optimizing diesel engine heterogeneous combustion performance and NOx emissions: A next energy perspective with AI by Aditya Kolakoti

“…The combustion results are trained in a feed-forward artificial neural network (ANN) algorithm for the predictions, and an error histogram with 20 bins helps identify the accuracy of the trained model. …”
Get full text