Optimalisasi Prediksi Harga Ihsg Menggunakan Hybrid Weighted Fuzzy Time Series Hidden Markov Model Dengan Algoritma Evolusi Differensial by Alya Fitri Syalsabilla, Suci Astutik, Agus Fachrur Rozy

“…Forecasting from the Hybrid WFTS-HMM Model with the DE Algorithm has lower prediction error (1.45%) compared to the model without DE (1.49%). …”
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Simulation and Test Study of Blast Crater in Deep Ore Body of Metal Mine Based on Lsdyna by Erhu Dong, Long An, Yuanhui Li, Jiahua Zhang

“…In this paper, a numerical simulation method under the fluid-solid coupling algorithm of rock body and explosive is constructed by combining the on-site blast crater test, Lsdyna JHC (Johnson Holmquist Concrete) damage model, and MATLAB parameter fitting algorithm. …”
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EBG Based Microstrip Patch Antenna for Brain Tumor Detection via Scattering Parameters in Microwave Imaging System by Reefat Inum, Md. Masud Rana, Kamrun Nahar Shushama, Md. Anwarul Quader

“…A monostatic radar-based confocal microwave imaging algorithm is applied to generate the image of tumor inside a six-layer human head phantom model. …”
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Re-locative guided search optimized self-sparse attention enabled deep learning decoder for quantum error correction by Umesh Uttamrao Shinde, Ravikumar Bandaru

“…For model tuning, this research utilizes the RIGS nature-inspired algorithm that mimics the re-locative, foraging, and hunting strategies, which avoids local optima problems and improves the convergence speed of the RlGS2-DCNTM for Quantum error correction. …”
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Stroke Lesion Prediction by Bille-Viper-Segmentation with Tandem-MU-net Model by Beevi Fathima, N Santhi Dr, N Ramasamy Dr

“…Furthermore, the Focus View Algorithm is suggested, which incorporates features from infarcted regions to improve early detection of emerging lesions. …”
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Estimating Network Flowing over Edges by Recursive Network Embedding by Liqun Yu, Hongqi Wang, Haoran Mo

“…We develop an iterative algorithm to learn the node embeddings, edge flows, and node values jointly. …”
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Visual Analysis of E-Commerce User Behavior Based on Log Mining by Tingzhong Wang, Nanjie Li, Hailong Wang, Junhong Xian, Jiayi Guo

“…The system uses dimensional modeling to build a data warehouse hierarchical system to mine and analyze user behavior data through log mining algorithm deeply. The K-means clustering algorithm and RFM model are used to divide the user behavior characteristics in detail, and AARRR funnel model is used to analyze the logs in a modular way. …”
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Research and development of integrated life cycle risk management and control platform for large petroleum storage depot by Xiping ZHU

“…Besides, an emergency rescue route optimization model for petroleum storage depots was built by improving the Dijkstra algorithm, and a fire analysis algorithm and an emergency drone platform were developed. …”
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Fuzzy Multicriteria Decision-Making Model for Time-Cost-Risk Trade-Off Optimization in Construction Projects by M. Ammar Alzarrad, Gary P. Moynihan, Muhammad T. Hatamleh, Siyuan Song

“…The algorithm was implemented in the MATLAB software and applied to two case studies to verify and validate the presented model. …”
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Intelligent health monitoring system based on smart clothing by Chung-Chih Lin, Chih-Yu Yang, Zhuhuang Zhou, Shuicai Wu

“…The system integrated our proposed fast empirical mode decomposition algorithm for electrocardiography denoising and hidden Markov model–based algorithm for fall detection. …”
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Detection and identification technology of rotor unmanned aerial vehicles in 5G scene by Fengtong Xu, Tao Hong, Jingcheng Zhao, Tao Yang

“…The noise interference is added to verify that the algorithm has better robustness. The micro-Doppler characteristics of rotor unmanned aerial vehicles are extracted by the above algorithm, and the data sets are built to train the model. …”
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Adaptive anti-jamming scheme based on meta-surface antenna by GUO Yuze, JIN Liang, XU Xiaoming, MA Keming, PEI Chen

“…Firstly, an improved sparsity adaptive matching pursuit (SAMP) algorithm was designed to estimate the direction of arrival (DOA). …”
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Sparse Regularization With Reverse Sorted Sum of Squares via an Unrolled Difference-of-Convex Approach by Takayuki Sasaki, Kazuya Hayase, Masaki Kitahara, Shunsuke Ono

“…These include developing an algorithm grounded in theory, not heuristics, reducing computational complexity, enabling the automatic determination of numerous parameters, and ensuring the number of iterations remains feasible. …”
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GRU-based multi-scenario gait authentication for smartphones by Qi JIANG, Ru FENG, Ruijie ZHANG, Jinhua WANG, Ting CHEN, Fushan WEI

“…At present, most of the gait-based smartphone authentication researches focus on a single controlled scenario without considering the impact of multi-scenario changes on the authentication accuracy.The movement direction of the smartphone and the user changes in different scenarios, and the user’s gait data collected by the orientation-sensitive sensor will be biased accordingly.Therefore, it has become an urgent problem to provide a multi-scenario high-accuracy gait authentication method for smartphones.In addition, the selection of the model training algorithm determines the accuracy and efficiency of gait authentication.The current popular authentication model based on long short-term memory (LSTM) network can achieve high authentication accuracy, but it has many training parameters, large memory footprint, and the training efficiency needs to be improved.In order to solve the above problems a multi-scenario gait authentication scheme for smartphones based on Gate Recurrent Unit (GRU) was proposed.The gait signals were preliminarily denoised by wavelet transform, and the looped gait signals were segmented by an adaptive gait cycle segmentation algorithm.In order to meet the authentication requirements of multi-scenario, the coordinate system transformation method was used to perform direction-independent processing on the gait signals, so as to eliminate the influence of the orientation of the smartphone and the movement of the user on the authentication result.Besides, in order to achieve high-accuracy authentication and efficient model training, GRUs with different architectures and various optimization methods were used to train the gait model.The proposed scheme was experimentally analyzed on publicly available datasets PSR and ZJU-GaitAcc.Compared with the related schemes, the proposed scheme improves the authentication accuracy.Compared with the LSTM-based gait authentication model, the training efficiency of the proposed model is improved by about 20%.…”
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Feature Extraction using Histogram of Oriented Gradients and Moments with Random Forest Classification for Batik Pattern Detection by wafiq azizah, soffiana agustin

“…These findings underscore the efficacy of integrating HOG and Texture Moments with the Random Forest algorithm for automated batik pattern recognition.…”
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Intelligent Digital Currency and Dynamic Coding Service System Based on Internet of Things Technology by Shanshen Li, Xin Jing

“…In this paper, the RDCAR algorithm is used to realize the routing discovery process of the wireless network. …”
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Selecting the Best Routing Traffic for Packets in LAN via Machine Learning to Achieve the Best Strategy by Bo Zhang, Rongji Liao

“…The shortest path is considered as the key issue in routing algorithm that can be carried out with real time of path computations. …”
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Vision-Based Damage Detection Method Using Multi-Scale Local Information Entropy and Data Fusion by Yiming Zhang, Zili Xu, Guang Li, Cun Xin

“…To tackle these challenges, we propose a novel vision-based damage detection method combining multi-scale signal analysis theory and data fusion algorithm. For high-spatial-resolution vibration measurements, phase-based optical flow estimation algorithm is adopted to deploy virtual sensors on the structure, yielding reliable mode shapes. …”
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Nondata-aided error vector magnitude based adaptive modulation over rapidly time-varying channels by Fan YANG, Xiao-ping ZENG, Xin JIAN, Ji-hua ZHOU, Ding-liang RUAN, Yi-wen GAO

“…A novel nondata-aided error vector magnitude based adaptive modulation(NDA-EVM-AM) was proposed to solve the problem of lower spectral efficiency over rapidly time-varying wireless channels.Namely,NDA-EVM was considered as a metric to reflect the rapid change of time-varying channels.The unified model to calculate different modulation order of NDA-EVM was analytically derived,with which the relationship between NDA-EVM and bit error rate (BER) for each modulation order was presented.Thereafter,the mechanism to adaptively select the modulation orders of multilevel quadrature amplitude modulation (MQAM) signals was designed to guarantee the predefined BER.Taking the two rapidly time-varying channels proposed for high-speed railway scenarios as examples,numerical results are conducted to verify the effectiveness of the proposed algorithm.It shows that NDA-EVM estimation has the lest root mean square error than data-aided error vector magnitude (DA-EVM) estimation and signal to noise ratio estimation.The proposed algorithm has better accuracy in aspects of channel quality estimation and modulation orders adjustment,Compared with conventional data-aided error vector magnitude based-adaptive modulation (DA-EVM-AM),the accuracy improves by 7.9%,spectral efficiency improves by 0.53 bit·s⁻¹·Hz⁻¹,and compared with signal to noise ratio based-adaptive modulation (SNR-AM),the accuracy improves by 15.7%,spectral efficiency improves by 0.82 bit·s⁻¹·Hz⁻¹.…”
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Optimal Mandatory Lane-Changing Location Planning for CAV Based on Cell Transmission Model by Gao Gao, Zhengfeng Huang, Wei Ji, Pengjun Zheng

“…We use the Ant Colony Optimization (ACO) algorithm to solve the problem. Through the case study of a basic two-lane road scenario in Ningbo, we acquire the convergence results based on the ACO algorithm. …”
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