Needle in a haystack: Harnessing AI in drug patent searches and prediction. by Leonardo Costa Ribeiro, Valbona Muzaka

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Bearing Fault Prediction Based on Mixed Domain Features and GWO-SVM by Xuan Zhou, Ruiyang Xia, Zhaodong Zhang, Sasa Duan, Mao Cheng, Chengjiang Zhou, Min Mao

“…Finally, aiming at improving the bearing fault prediction accuracy, the GWO algorithm is used to optimize the parameters. …”
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PV Polaris – Automated PV System Orientation Prediction by Ernst Wittmann, Claudia Buerhop-Lutz, Savannah Bennett, Vincent Christlein, Jens Hauch, Christoph J. Brabec, Ian Marius Peters

“…This study introduces an automated Monte Carlo Search based algorithm called PV Polaris which is capable of predicting the systems orientation within 18 s, with uncertainties of less than 2° in tilt and 4° in azimuth. …”
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Using Backpropagation to Predict Drought Factor in Keetch-Byram Drought Index by Hadisuwito et al.

“…Therefore, we need an algorithm that can predict the dryness factor. So, the most significant fire potential can be predicted during the dry season. …”
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Quality Prediction Model Based on Novel Elman Neural Network Ensemble by Lan Xu, Yuting Zhang

“…In this paper, we propose a novel prediction algorithm based on an improved Elman neural network (NN) ensemble for quality prediction, thus achieving the quality control of designed products at the product design stage. …”
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Cost Index Predictions for Construction Engineering Based on LSTM Neural Networks by Jiacheng Dong, Yuan Chen, Gang Guan

“…The present study proposed a new framework based on LSTM, so as to explore the applicability and optimization mechanism of the algorithm in the field of cost indexes prediction. …”
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The TB27 Transcriptomic Model for Predicting Mycobacterium tuberculosis Culture Conversion by Maja Reimann, Korkut Avsar, Andrew DiNardo, Torsten Goldmann, Gunar Günther, Michael Hoelscher, Elmira Ibraim, Barbara Kalsdorf, Stefan Kaufmann, Niklas Köhler, Anna Mandalakas, Florian Maurer, Marius Müller, Dörte Nitschkowski, Ioana Olaru, Cristina Popa, Andrea Rachow, Thierry Rolling, Helmut Salzer, Patricia Sanchez-Carballo, Maren Schuhmann, Dagmar Schaub, Victor Spinu, Elena Terhalle, Markus Unnewehr, Nika Zielinski, Jan Heyckendorf, Christoph Lange

“…Methods: Using a multi-step machine learning algorithm to identify an RNA-based algorithm to predict the remaining time to culture conversion at flexible time points during anti-tuberculosis therapy.  …”
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Human Heart Disease Prediction System Using Data Mining Techniques by Sidra Javed, Hamza Javed, Ayesha Saddique, Beenish Rafiq

“…To address this problem, Decision Tree is used to predict the heart disease. In this study the collected data is pre-processed, Decision Tree algorithm and ID3 were then applied to predict the heart disease.   …”
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Career path prediction using XGBoost Model and students’ academic results by Hong Quan Nguyen, Duc Dang Khoi Nguyen, Tan Duy Le, An Mai, Kha Tu Huynh

“…Initially, the dataset is cleaned up and normalized to be usable for the prediction algorithm with the help of Python 3 programming language. …”
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Career path prediction using XGBoost Model and students’ academic results by Hong Quan Nguyen, Duc Dang Khoi Nguyen, Tan Duy Le, An Mai, Kha Tu Huynh

“…Initially, the dataset is cleaned up and normalized to be usable for the prediction algorithm with the help of Python 3 programming language. …”
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Hysteretic curve characteristics in rectangular shear walls predicted by machine learning by Jungui Dong, Ce Chen

“…An interpretable empirical guidance machine learning (IEG-ML) was proposed for predicting these feature points. IEG-ML aligns with empirical trends from extensive experiments and is explainable via explicit formulas. …”
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Analysis and prediction of infectious diseases based on spatial visualization and machine learning by Yunyun Cheng, Yanping Bai, Jing Yang, Xiuhui Tan, Ting Xu, Rong Cheng

“…Finally, a multi algorithm fusion learning model based on stacking technology is proposed to address the problem of poor generalization ability of single algorithm models in prediction; Furthermore, radial basis function network (RBF) was used as a two-level meta learner to fuse the above models, and particle swarm optimization (PSO) was used to optimize RBF parameters to reduce generalization error. …”
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Research on Credit Default Prediction Model Based on TabNet-Stacking by Shijie Wang, Xueyong Zhang

“…With the development of financial technology, the traditional experience-based and single-network credit default prediction model can no longer meet the current needs. …”
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An Inference Framework of Markov Logic Network for Link Prediction in Heterogeneous Networks by Zhongbin Li, Kun Yue, Lixing Yu, Jiahui Wang

“…The presence of multiplex edges and sparse links often hampers the efficacy of link prediction (LP) tasks. By harnessing the expressive power of Markov logic network (MLN) formulations, multiplex edges can be unified to enhance LP effectiveness. …”
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Prediction of Train Arrival Delay Using Hybrid ELM-PSO Approach by Xu Bao, Yanqiu Li, Jianmin Li, Rui Shi, Xin Ding

“…Next, an ELM with one hidden layer is developed to predict train arrival delays by considering these characteristics mentioned before as input features. …”
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Modelling and Prediction of Random Delays in NCSs Using Double-Chain HMMs by Yuan Ge, Yan Zhang, Wengen Gao, Fanyong Cheng, Nuo Yu, Jincenzi Wu

“…This paper is concerned with the modelling and prediction of random delays in networked control systems. …”
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Automatic determination of the frequency behaviour of the larynx tone by the method of linear prediction by Andrzej DZIURNIKOWSKI

“…This paper presents a method of automatically tracing the frequency of the larynx tone, based on a numerical implementation of the method of linear prediction on a digital computer. It also discusses the algorithm for the practical implementation of this method, derived by the author, and presents the results obtained from the analysis of a continuous speech signal with a duration of approximately 2 seconds.…”
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The Impact of Prediction Models on Energy-Aware Resource Management in FaaS Platforms by Shahrokh Vahabi, Francesca Righetti, Carlo Vallati, Nicola Tonellotto

“…Moreover, resource allocation performed through the EA-RM algorithm reduces the energy consumption by ~12-45% on average w.r.t. competitors, and is proven to be more robust w.r.t. the accuracy of the prediction model used.…”
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Prediction of permeability and effective porosity values using ANN in Maleh field by Mohammed Essa Nassani, Ali Alaji

“…The ANN was tested on independent data and demonstrated exceptional performance, achieving 96% accuracy for effective porosity and 98% for permeability predictions in sandstone formations. This efficient algorithm eliminates the need for core sample analysis, reducing costs and time while improving prediction reliability, making it a valuable tool for subsurface characterization and resource exploration.…”
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Development and Validation of a Dynamic Prediction Model for Massive Hemorrhage in Trauma by Chengyu Guo, Maolin Tian, Minghui Gong, Fei Pan, Hui Han, Chunping Li, Tanshi Li

“…This study developed and validated a group of dynamic prediction models based on vital sign time-series data and a deep-learning algorithm to assist medical staff in the early diagnosis and dynamic prediction of a future massive hemorrhage in trauma.…”
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