A Collaborative Filtering Recommendation Algorithm Based on User Confidence and Time Context by Guangxia Xu, Zhijing Tang, Chuang Ma, Yanbing Liu, Mahmoud Daneshmand

“…Finally, the experimental results demonstrate that the proposed algorithm is suitable for the sparse data and effectively improves the prediction accuracy and enhances the recommendation quality at the same time.…”
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Design and Research of Skin Injection Molded TPE Materials Based on Genetic Algorithm by Kui Yan, Yizhe Chen, Hui Wang, Cheng Gao, Qiuyang Bai

“…In this study, the TPE material was prepared using different mass ratios with homopolymer polypropylene (PP), styrene-ethylene/butene-styrene copolymer (SEBS), naphthene oil (NO), magnesium stearate (MGST), and polytetrafluoroethylene (PTFE). A quality-prediction and multiobjective optimization method based on a genetic algorithm was applied. …”
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Combined multiple random features least mean square algorithm for online applications by Minglin Shen, Wei Feng, Gangyi Huang, Letian Qi, Yu Liu, Shiyuan Wang

“…CMRFLMS with a fixed dimensional network structure can provide comparable performance and faster convergence rate than MKLMS. Simulations on prediction of synthetic and real non‐linear system identification illustrate the superiorities of the proposed CMRFLMS algorithm from the aspects of filtering accuracy, convergence rate, and tracking performance.…”
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AUGUR, a flexible and efficient optimization algorithm for identification of optimal adsorption sites by Ioannis Kouroudis, Poonam, Neel Misciasci, Felix Mayr, Leon Müller, Zhaosu Gu, Alessio Gagliardi

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Intelligent guarantee power supply decision method based on reinforcement learning algorithm by Milu Zhou, Huijie Sun, Tian Yang, Tingting Li, Qi Hou

“…Abstract Traditional power supply decision methods rely on fixed and rigorous mathematical models, which are difficult to accurately capture the characteristics and changing patterns of new loads, resulting in low prediction accuracy. Therefore, a decision model for guaranteeing power supply is constructed based on an improved proximal policy optimization algorithm, to study the intelligent guarantee power supply decision method. …”
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Classification algorithm for imbalance data of ECG based on PSOFS and TSK fuzzy system by Xinhui LI, Qing SHEN, Xiongtao ZHANG

“…., parallel ensemble fuzzy neural network based on PSOFS and TSK (PE-PT-FN), which was used for ECG prediction.Each class sample in the training set was randomly sampled, and the samples obtained by randomly sampled were added.Then, the feature selection method PSOFS was carried out independently and parallelly.In PSOFS, particles that were random initial positions represent different feature subsets and converge to the optimal positions after many iterations.Each subset had a corresponding feature subset.Several groups of TSK fuzzy neural network (TSK-FNN) were trained by each feature subset in parallel.Medical researchers could effectively find the correlation between ECG signal data and different types of disease through the interpretability of the fuzzy system and the feature subsets by the PSOFS algorithm.Experiments prove that PE-PT-FN greatly improves the macro-R to 92.35% while retaining interpretability.…”
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Research on Parameter Extraction Method of Photovoltaic Module Based on Improved Hybrid Algorithm by Haitao Wu, Zhou Shang

“…Firstly, the analytical method is applied to simplify the equivalent circuit model and improve the efficiency of the algorithm. Then, the adaptive algorithm is used to adjust the parameters of the differential evolution algorithm. …”
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Recognizing Cow Muzzle Patterns using the Convolution Neural Network (CNN) Algorithm by Sulthon Zamroni, Giri Wahyu Wiriasto, Bulkis Kanata

“…Numerous systems and algorithms have been developed to recognize cattle, ranging from body shape, fur patterns, to specific parts of the cattle. …”
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Application of the ABC Algorithm in Parameter Estimation and Kinetic Model Selection in Propionic Fermentation by Waldecleia Queiroz Da Costa, Miguel Fernando Saraiva Maia, Nilton Pereira Da Silva, Deibson Silva Da Costa, Emerson Cardoso Rodrigues, Diego Cardoso Estumano

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ALGORITHM OF DECISION GIVEN COMBINATORIAL TASKS ON THE BASE OF MANY-CRITARIAL OPTIMIZATION MODEL by S. V. Chebakov, L. V. Serebryanaya

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Bayesian Robust Tensor Decomposition Based on MCMC Algorithm for Traffic Data Completion by Longsheng Huang, Yu Zhu, Hanzeng Shao, Lei Tang, Yun Zhu, Gaohang Yu

“…In this paper, a Bayesian robust tensor decomposition method (MBRTF) based on the Markov chain Monte Carlo (MCMC) algorithm is proposed. The underlying low CANDECOMP/PARAFAC (CP) rank tensor captures the global information, and the sparse tensor captures local information (also regarded as anomalous data), which achieves a reliable prediction of missing terms. …”
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Pothole Detection and Assessment on Highways Using Enhanced YOLO Algorithm With Attention Mechanisms by Rufus Rubin, Chinnu Jacob, Sumod Sundar, Gabriel Stoian, Daniela Danciulescu, Jude Hemanth

“…It enhances detection by modifying the YOLO algorithm, using the Xception backbone, and integrating attention mechanisms to improve the prediction of small or clustered objects. …”
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Rapid Assessment of the Fatigue Limit Using an Iterative Algorithm Applied to Intrinsic Dissipation by Luca Santoro, Raffaella Sesana, Francesca Maria Curà

“…The aim of this paper is to introduce and validate an iterative algorithm for the rapid assessment of the fatigue limit. …”
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Multiobjective Optimization Method for Polymer Injection Molding Based on a Genetic Algorithm by Zhijun Yuan, Hui Wang, Xuebing Wei, Kui Yan, Cheng Gao

“…To solve the quality problem of polymer injection parts, a quality prediction and multiobjective optimization method is established. …”
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Compressive sensing based data gathering algorithm over unreliable links in WSN by Ce ZHANG, Xia ZHANG, Ou LI, Guan-lin MEI, Zhe HAN, Da-long ZHANG, Guang-yi LIU

“…To solve the problem that the ubiquitous unreliable links in the WSN influence the performance of the compressive sensing (CS) based data gathering,first the relationship between the reconstruction SNR of CS-based data gathering algorithm and the bit-error-ratio (BER) were simulated quantitatively.Then classify two cases were classified,namely light-payload and heavy-payload,relying on the analysis of wireless link packet loss characteristics.The random packet loss model was conceived to describe the packet loss under light-payload scenario.Further the neighbor topology spatial correlation prediction-based CS data gathering (CS-NTSC) algorithm was proposed,which utilized the nodes spatial correlation to reduce the impact of error.Additionally,the node pseudo-failure model was conceived to describe the packet loss occurred in network congestion,and then the sparse schedule-aided CS data gathering (CS-SSDG) algorithm were conceived,for the purpose of changing the sparsity of measurement matrix and avoiding measurements amongst the nodes affected by unreliable links,thus weakening the impact of error/loss on data reconstruction.Simulation analysis indicates that the proposed algorithms are not only capable of improving the accuracy of the data reconstruction without extra energy,but also effectively reducing the impact affected by the unreliable links imposed on CS-based data gathering.…”
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Aerodynamic Shape Optimization of a Missile Using a Multiobjective Genetic Algorithm by Ahmet Şumnu, İbrahim Halil Güzelbey, Orkun Öğücü

“…Multiobjective Genetic Algorithm (MOGA) was used to optimize missile geometry. …”
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Moldina: a fast and accurate search algorithm for simultaneous docking of multiple ligands by Radek Halfar, Jiří Damborský, Sérgio M. Marques, Jan Martinovič

“…Here we present Moldina (Multiple-Ligand Molecular Docking over AutoDock Vina), a new algorithm built upon AutoDock Vina. Through comprehensive testing against AutoDock Vina, the algorithm exhibited comparable accuracy in predicting ligand binding conformations while significantly reducing the computational time up to several hundred times. …”
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Intelligent analysis algorithm for power engineering data based on improved BiLSTM by Yuanyuan Xu, Jiapeng Yang, Xin Cai

“…Abstract Traditional BiLSTM (Bidirectional Long Short-Term Memory) has limited processing capabilities for long-time series, insufficient adaptability to the characteristics of power engineering data, and inadequate accuracy in predicting problems in specific application scenarios. …”
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Research on Fast Algorithm of Radio Wave Propagation in Low-Lossy Obstacles Environment by An-qi Li, Cheng-you Yin, Qian-qian Zhang, Yong-ji Gan

“…After that, we explain the algorithm steps in the process of calculating the total field, compared with the traditional 2W-PE, and then finally introduce the method of moments (MoM) combined with the enhanced discrete complex image (E-DCIM) method for accuracy verification of the new 2W-PE algorithm. …”
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Ultra-Short Wave Communication Squelch Algorithm Based on Deep Neural Network by Yuanxin Xiang, Yi Lv, Wenqiang Lei, Jiancheng Lv

“…The proposed algorithm first predicts the speech existence probability using a three-layer Gated Recurrent Unit (GRU) with the speech banding spectrum as the feature. …”
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