Highway subgrade stability prediction model based on depth separation convolutional fusion network by Yubian Wang

“…According to the error between the current prediction result and the real result, the contribution of each neuron to the error is calculated in reverse. …”
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Data-driven machine learning algorithm model for pneumonia prediction and determinant factor stratification among children aged 6–23 months in Ethiopia by Addisalem Workie Demsash, Rediet Abebe, Wubishet Gezimu, Gemeda Wakgari Kitil, Michael Amera Tizazu, Abera Lambebo, Firomsa Bekele, Solomon Seyife Alemu, Mohammedamin Hajure Jarso, Geleta Nenko Dube, Lema Fikadu Wedajo, Sanju Purohit, Mulugeta Hayelom Kalayou

“…Therefore, this study aimed to develop data-driven predictive model using machine learning algorithms to predict pneumonia and stratify the determinant factors among children aged 6–23 months in Ethiopia. …”
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Melanoma risk prediction models by Nikolić Jelena, Lončar-Turukalo Tatjana, Sladojević Srđan, Marinković Marija, Janjić Zlata

“…The aim of this study was to identify most significant factors for melanoma prediction in our population and to create prognostic models for identification and differentiation of individuals at risk. …”
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Adjacency List Algorithm for Traffic Light Control Systems in Urban Networks by Sergio Rojas-Blanco, Alberto Cerezo-Narváez, Manuel Otero-Mateo, Sol Sáez-Martínez

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Predicting pregnancy loss and its determinants among reproductive-aged women using supervised machine learning algorithms in Sub-Saharan Africa by Tirualem Zeleke Yehuala, Sara Beyene Mengesha, Nebebe Demis Baykemagn

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Prediction of old goaf residual subsidence integrating EDS-InSAR with EsLSTM in the Loess Plateau, China by Fei Ma, Fei Ma, Qingbin Zhang, Lichun Sui

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A Dual Filter Based on Radial Basis Function Neural Networks and Kalman Filters with Application to Numerical Wave Prediction Models by Athanasios Donas, Ioannis Kordatos, Alex Alexandridis, George Galanis, Ioannis Th. Famelis

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Predicting cardiovascular outcomes in Chinese patients with type 2 diabetes by combining risk factor trajectories and machine learning algorithm: a cohort study by Qi Huang, Xiantong Zou, Zhouhui Lian, Xianghai Zhou, Xueyao Han, Yingying Luo, Shuohua Chen, Yanxiu Wang, Shouling Wu, Linong Ji

“…Conclusions The ML-CVD-C model, incorporating dynamic cardiovascular risk trajectories and a machine learning algorithm, significantly improves risk prediction accuracy for Chinese patients with diabetes. …”
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Rapid screening of fumonisins in maize using near-infrared spectroscopy (NIRS) and machine learning algorithms by Bruna Carbas, Pedro Sampaio, Sílvia Cruz Barros, Andreia Freitas, Ana Sanches Silva, Carla Brites

“…This study evaluates the potential of near-infrared (NIR) spectroscopy combined with chemometric algorithms to detect fumonisins in maize. For fumonisin B1 (FB1) and B2 (FB2) levels were developed predictive NIR models using partial least squares (PLS) and artificial neural networks (ANN). …”
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Implementing a transmural model of early palliative care in advanced dementia: the use of a hybrid effectiveness-implementation study design by Allyn Hum, Palvinder Kaur, Wen Yang Goh, Riyin Tay, Han Yee Neo, Mervyn Yong Hwang Koh, Noorhazlina Binte Ali, Wee Shiong Lim, Yu-Ling Jackie Tan, Huei Yaw Wu, Palvannan Kannapiran, Hwee Teng Robyn Tan, Yan Sun, Chin Ee Ong, Ravinder Singh Sachdev, Zhi Jun Low, Lee Hung Tey, Woan Shin Tan, Yew Yoong Ding

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Algorithmic Literacy and the Role of Librarians in Its Education by Shahnaz Khademizadeh, Mohammad Amin Sekhavatmanesh

“…Objective: Considering the increasing spread of artificial intelligence and its algorithm-oriented nature and the increasing interaction of users with these algorithms in various platforms such as social networks, online stores, and search engines, the present study intends to examine the concept and necessity of algorithmic literacy and, in the following, the role of librarians who are actually specialists in information science in the education and development of this literacy. …”
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Research on the Application of Genetic Algorithm in Physical Education by Haibo Wang

“…A large number of experiments have proved that the proposed algorithm meets all the requirements of physical education very well. …”
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Parallel Attribute Reduction Algorithm for Complex Heterogeneous Data Using MapReduce by Tengfei Zhang, Fumin Ma, Jie Cao, Chen Peng, Dong Yue

“…Thereafter, a quick parallel attribute reduction algorithm using MapReduce was developed. …”
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Regeneration Filter: Enhancing Mosaic Algorithm for Near Salt & Pepper Noise Reduction by Ratko M. Ivković, Ivana M. Milošević, Zoran N. Milivojević

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Unsustainable artificial intelligence and algorithmically facilitated emissions: The case for emissions-reduction-by-design by Jutta Haider, Malte Rödl, James White

“…It introduces the notion of algorithmically facilitated emissions to initiate a shift from a logic of ‘climate collapse by design’ to a logic of ‘emissions reduction by design’. …”
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Improved HLLL Lattice Basis Reduction Algorithm to Solve GNSS Integer Ambiguity by Kezhao Li, Chendong Tian, Yingxiang Jiao, Zhe Yue

“…Compared with the LLL reduction algorithm and HLLL reduction algorithm, the experimental results show that the PHLLL algorithm has higher reduction efficiency and effectiveness. …”
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Optimization Algorithm of Workflow’s Accuracy Based  on Serial Reduction under Constraint Time by LUO Zhi-yong, ZHU Zi-hao, YOU Bo, MIAO Shi-di

“…Finally，in the typical case，the traditional one-way target algorithm and the string reduction algorithm are used to solve the corresponding path respectively， and analyzed the other parameters that affect the performance of SＲA. …”
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Neighborhood conditional mutual information entropy attribute reduction algorithm for hybrid data by Haibo LAN

“…Attribute reduction is an important research content of the rough set theory.Its main purpose is to eliminate irrelevant attributes in information systems, reduce data dimensions and improve data knowledge discovery performance.However, most of the attribute reduction methods based on a rough set do not consider the dependence between attributes, which makes the final attribute reduction result have some redundant attributes.An attribute reduction algorithm based on neighborhood conditional mutual information entropy was proposed.Firstly, based on the traditional neighborhood entropy, a hybrid neighborhood mutual information entropy model and a hybrid neighborhood conditional mutual information entropy model were proposed for hybrid data.Then, the two entropy models were used to evaluate the attribute dependence and attribute heuristic search of the hybrid information system, and an attribute reduction algorithm was designed.Finally, through the experimental analysis of UCI data sets, it was proved that the algorithm had higher attribute reduction performance.…”
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Improved Crosstalk Reduction on Multiview 3D Display by Using BILS Algorithm by Xiaoyan Wang, Chunping Hou

“…In this paper, we present a system-introduced crosstalk measurement method and derive an improved crosstalk reduction method. The proposed measurement method is applied to measure the exact crosstalk among subpixels corresponding to different view images and the obtained results are very effective for crosstalk reduction method. …”
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Incremental attribute reduction algorithm for dominance-based neighborhood relative decision entropy by CHEN Baoguo, CHEN Lei, DENG Ming, LI Xiaoyan, CHEN Jinlin

“…Verify the effectiveness of the incremental algorithm through these experimental results.ConclusionsThe experimental results show that the proposed incremental algorithm has better attribute reduction performance on dynamic datasets, significantly improving the efficiency of dynamic attribute reduction while ensuring the number of attribute selections and classification accuracy. …”
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