Deep Learning Algorithm-Based Financial Prediction Models by Helin Jia

“…The combined forecasting model proposed in this paper is based on the idea of decomposition-reconstruction synthesis, which effectively improves the model’s prediction of internal financial time series. In this paper, we select the CSI 300 Index and foreign exchange rate as the empirical market and data and establish seven forecasting models to make predictions about the short-term running trend of the closing price. …”
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Financial distress prediction in Slovakia: An application of the CART algorithm by Marek Durica, Jaroslav Frnda, Lucia Svabova

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Integration of Genetic Algorithm with Machine Learning for Properties Prediction by Rathachai Chawuthai, Siripan Murathathunyaluk, Nalin Amornratthamrong, Run Arunchaipong, Amata Anantpinijwatna

“…Consequently, ML’s predictive capabilities have been extended to encompass a broader range of properties, including Partition Coefficient, Boiling Point, and Solubility, among others, for oxygenated hydrocarbon derivatives. …”
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Prediction Method of Lithology Log Based on XGBoost Algorithm by CHU Qingjun, GE Yunlong, TONG Maosong, WANG Yan, AN Lyuxing, YU Chuanwu, JIA Xin

“…To solve this problem, an XGBoost algorithm-based model for predicting the photoelectric absorption cross-section index is established, and its prediction effect is compared with that of a neural network algorithm model. …”
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5G network slicing algorithm based on prediction by Jiageng ZHANG, Min ZHU, Feng DU, Qi WANG, Jun LIU, Zhihai SUO, Li WANG

“…5G on line scenario needs short build time of network slice, it can use prediction algorithm to isolate network resource in advance to reduce the construction time of network slice.A 5G network slicing algorithm based on prediction was proposed, which used fourth square as cost function to predict the network resource requests with accepted accurate and lower complexity of algorithm.And then based on the prediction result, virtual nodes and links resource were allocated, and container was pulled up when network slice request arrives to network, the dynamic creation of network slices was completed.The simulation results show that the proposed algorithm can get 90% accurate of prediction, and reduce 50% construction time of network slice, and improve the network utilization ration，when new network slice reusing the original network slice.…”
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Terrain Simplification Algorithm in Radio Wave Propagation Prediction by Dan Shi, Zhen Zhang, Fengshuo Wei, Cheng Lian

“…In order to study the influence of terrain simplification on the prediction of complex electromagnetic environment, a visibility algorithm used in the regular model of terrain and a probability-based power propagation model are proposed. …”
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DATA MINING ALGORITHMS FOR PREDICTION OF STUDENT TEACHERS’ PERFORMANCE IN ICT: A SYSTEMATIC LITERATURE REVIEW by Juma Habibu Shindo, Mohamedi Mohamedi Mjahidi, Mohamed Dewa Waziri

Subjects: “…data mining algorithms…”
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Naïve Bayes is an interpretable and predictive machine learning algorithm in predicting osteoporotic hip fracture in-hospital mortality compared to other machine learning algorithms. by Jo-Wai Douglas Wang

“…Overall, NB has much potential as an algorithm, due to its simplicity and interpretability whilst maintaining competitive predictive performance.…”
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Steiner eccentricity: Predictions and applications by Xingfu Li, Zongbo Yang, Siyi Lin, Jialu Wang

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Spatial Distribution of Poverty Clusters and Its Prediction Algorithms: A Visual Analytics Approach to Understanding the Disparities of Poverty Across Zones by Ngong'ho Bujiku Sende, Snehanshu Saha, Leon Fidele Ruganzu Uwimbabazi

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Appropriate Combination of Artificial Intelligence and Algorithms for Increasing Predictive Accuracy Management by Shahram Gilani Nia

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Resolving the Credibility Crisis: Recommendations for Improving Predictive Algorithms for Clinical Utility by Stephen Ruberg, Sandeep Menon, Charmaine Demanuele

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Predictive for patients with pneumonia in pediatric intensive care unit by Mingxuan Jia, Xiyan Hu, Lin Ji, Jiawen Lin, Jialin Liu, Yong Wang

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Predicting Bank Loan Risks Using Machine Learning Algorithms by Maan Alsaleem, Safwan Hasoon

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Chaos Time Series Prediction Based on Membrane Optimization Algorithms by Meng Li, Liangzhong Yi, Zheng Pei, Zhisheng Gao, Hong Peng

“…This paper puts forward a prediction model based on membrane computing optimization algorithm for chaos time series; the model optimizes simultaneously the parameters of phase space reconstruction (τ,m) and least squares support vector machine (LS-SVM) (γ,σ) by using membrane computing optimization algorithm. …”
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Spatiotemporal data modeling and prediction algorithms in intelligent management systems by Xin Cao, Chunxiao Mei, Zhiyong Song, Hao Li, Jingtao Chang, Zhihao Feng

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Application of machine learning algorithms in predicting pyrolytic analysis result by Thi Nhut Suong Le, A. V. Bondarev, L. I. Bondareva, A. S. Monakova, A. V. Barshin

“…In this paper, machine learning regression algorithms are applied for predicting one of the pyrolysis parameters of extracted samples based on the pyrolytic analysis results of the extracted and non-extracted samples. …”
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Chronic Kidney Disease Prediction Based On Machine Learning Algorithms by Kethineni Likitha., Nithinchandra, Kumar Narendra, Sk Sajida Sultana.

“…This paper analyses the suitability of several machine learning algorithms for CKD prediction in consideration of health-related parameters like age, blood pressure, and blood glucose levels. …”
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A novel model for malaria prediction based on ensemble algorithms. by Mengyang Wang, Hui Wang, Jiao Wang, Hongwei Liu, Rui Lu, Tongqing Duan, Xiaowen Gong, Siyuan Feng, Yuanyuan Liu, Zhuang Cui, Changping Li, Jun Ma

“…However, a stacking architecture can solve this problem by combining distinct algorithms and models. This study compares the performance of traditional time series models and deep learning algorithms in malaria case prediction and explores the application value of stacking methods in the field of infectious disease prediction.…”
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Application of Artificial Intelligence Algorithms in the Field of Antimicrobial Peptide Prediction by QIAN Yuchen, NIE Ting, HUA Yanming, XU Shiying, GUO Sheng, ZHANG Xin, LUO Xiaohu, LIU Yanan

“…Artificial intelligence algorithms can be continuously optimized based on prior knowledge and real-time data, which significantly improves the prediction efficiency of antibacterial peptides and reduces research and development costs. …”
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