Forecasting the vapor pressure deficit in vertical farming facilities aiming to provide optimal indoor conditions by Carlos Alejandro Perez Garcia, Dafni Despoina Avgoustaki, Enrica Santolini, Daniele Torreggiani, Thomas Bartzanas, Patrizia Tassinari, Marco Bovo

“…This research develops and validates a prediction model based on NeuralProphet algorithm to assess the vapor pressure deficit in a vertical farming facility. …”
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Machine Learning-Based Cost Estimation Models for Office Buildings by Guolong Chen, Simin Zheng, Xiaorui He, Xian Liang, Xiaohui Liao

“…This paper explores the application of algorithm-optimized back propagation neural networks and support vector machines in predicting the costs of office buildings. …”
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A fast identification method for multi-joint robot load based on improved Fourier neural network by Xia Yue, Jionghao Mo, Zhibin Li, Haiteng Li, Chunliang Zhang, Shangbin Long

“…It only needs to learn several alternate sample sets in the prediction range, and any results in the prediction range can be accurately identified with good generalization ability. …”
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Classification and Application of Roof Stability of Bolt Supporting Coal Roadway Based on BP Neural Network by Heng Ren, Yongjian Zhu, Ping Wang, Peng Li, Yuqun Zhang, Xizhi Wang, Yingying Li

“…Through on-site investigation, numerical analysis, and other research methods, 6 evaluation indicators were determined, and according to the relevant evaluation factors and four types of coal roadway roof stability, a neural network structure for roof stability prediction was constructed to realize the quantitative prediction of the roof stability of bolt-supported coal roadway. …”
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EXPERT SYSTEM OF CLINICAL DIAGNOSTICS ACUTE SURGICAL ABDOMINAL PATHOLOGY by E. M. Lashkevich

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Modeling of a Tethered Testbed for a VTVL Vehicle by Marco Sagliano, Stephan Theil, Johanna Schramm, Matthias Schwarzwald

“…This paper proposes an algorithm for modeling a three-dimensional tethered environment for testing vertical-take off, vertical landing vehicles. …”
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Processing and analysis of images of microstructure metals for determining the grain point by R. P. Bohush, Y. R. Adamousky, S. F. Denisenak

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IT Parkinson’s Disease Diagnostics Based on the Freezing of Gait Analysis Using Long Short Term Memory Neural Network by U. A. Vishniakou, Xia YiWei

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ADAPTIVE FILTERING A NON-STATIONARY STRUCTURAL SIGNAL by D. L. Khodyko, S. B. Salomatin

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OPTIMIZATION OF A LASER TELEMETRIC SYSTEM PHOTORECEIVING MODULE by K. V. Melnikov

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Quantitative sub-ice and marine tracing of Antarctic sediment provenance (TASP v1.0) by J. W. Marschalek, E. Gasson, T. van de Flierdt, C.-D. Hillenbrand, M. J. Siegert, M. J. Siegert, L. Holder

“…These results show that the algorithm could be used to predict the provenance signature of past ice sheet configurations. …”
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METHOD OF EMOTION RECOGNITION USING model of key distance distribution by A. V. Zhabinski

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Modeling the Relationship Between Radon Anomalies and Seismic Activity Using Artificial Neural Networks and Statistical Methods by Kostadin Yotov, Emil Hadzhikolev, Stanka Hadzhikoleva

“…The methodology includes wavelet transformation for noise removal, a multilayer ANN trained using the Levenberg–Marquardt algorithm, and a segmentation approach based on radial zones (annuli) for localized predictions. …”
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Comparing machine learning approaches for estimating soil saturated hydraulic conductivity. by Ali Akbar Moosavi, Mohammad Amin Nematollahi, Mohammad Omidifard

“…Since the associated laboratory/field experiments are time-consuming and labor-intensive, pedotransfer functions (PTFs) that rely on statistical predictors are usually integrated with the existing measurements to predict Kfs in other areas of the field. In this study some of the most appropriate machine learning approaches, including variants of artificial neural networks (ANNs) were used for predicting Kfs by some easily measurable soil attributes. …”
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Calibration and uncertainty quantification for deep learning-based drought detection by Mengxue Zhang, Miguel-Ángel Fernández-Torres, Kai-Hendrik Cohrs, Gustau Camps-Valls

“…To address this shortcoming, we introduce methodologies for model calibration and entropy-based uncertainty quantification for deep learning-based drought detection. The calibration algorithm can deal with calibration errors by reducing distributional shifts and alleviating overconfident predictions. …”
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Advancing eHealth in Society 5.0: A Fuzzy Logic and Blockchain-Enhanced Framework for Integrating IoMT, Edge, and Cloud With AI by Joy Dutta, Deepak Puthal

“…We introduce the Health Prediction using Cloud Edge 2.0 (HPCE 2.0) algorithm, which employs fuzzy logic to effectively combine historical Electronic Health Records (EHRs) with real-time IoMT data, providing precise and personalized health severity level predictions. …”
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Hybrid Artificial Neural Network Activation Function to Reduce Water Wastage in Agricultural Irrigation by Baraa H. Jawad, Ola A. Alwesabi, Nibras Abdullah, Ahmed Abed Mohammed

“…The study proposes a hybrid activation function based on the Artificial Neural Network algorithm. This function is used to classify the need for irrigation in various crops and predict the best time of the day for watering. …”
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Promoter Region and Regulatory Elements of IGF and VIP Genes Associated With Reproductive Traits in Chicken by Bosenu Abera, Hunduma Dinka, Hailu Dadi, Habtamu Abera

“…Several in silico tools, such as Neural Network Promoter Prediction (NNPP), Multiple Expectation maximizations for Motif Elicitation (MEME-Suite), GC-Profiles, microsatellite prediction (MISA-web), CLC Genomics, Multiple Association Network Integration Algorithm (GeneMANIA), and Gene Ontology for Motifs (GOMO), were used to characterize the promoter regions and regulatory elements of IGF and VIP genes. …”
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Machine learning developed immune-related exosome signature for prognosis and immunotherapy benefit in bladder cancer by Xiaoting Luo, Yi Luo

“…To investigate the performance of IES in predicting the immunotherapy benefit, three immunotherapy datasets (GSE91061, GSE78220 and IMvigor210) and several predicting scores were used. …”
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Tumor associated neutrophils promote prostate cancer progression by mediating neutrophil trap secretion through PSMA1- NF-κB-HIF-1α signaling axis by Qian Dai, Qian Dai, Hua Wang, Hua Wang, Fang Li, Fang Li, Runchun Huang, Runchun Huang, Chenjun Jiang, Chenjun Jiang, Liuya Yuan, Liuya Yuan, Yayun Wang, Yayun Wang, Xun Li, Xun Li

“…Prostate cancer (PCa) is a common and deadly cancer in men, and despite its low specificity, PSA testing is the main method that is used to predict prognosis. Effective methods for predicting prognosis in clinical practice are lacking. …”
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