The complex seepage laws and high production costs in tight oil reservoirs have prompted scholars to apply machinelearning methods to optimize construction plans and predict development results. The machinelearning ...
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People's daily lives are getting more and more entangled with the Internet as technology advances and the level of living rises. The diversity of mobile Internet applications has also attracted some unscrupulous e...
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The development of today's society is inseparable from the continuous renewal of science and technology. As an important indicator of scientific and technological innovation, patents reflect the core competitivene...
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In response to the limited data coverage and lack of personalized learning among students in English education, vocabulary analysis was conducted utilizing the Long Short-Term Memory (LSTM) algorithm. By improving the...
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ISBN:
(纸本)9798400718144
In response to the limited data coverage and lack of personalized learning among students in English education, vocabulary analysis was conducted utilizing the Long Short-Term Memory (LSTM) algorithm. By improving the accuracy and efficiency of vocabulary analysis, deepening the understanding of student learning processes, and other methods, traditional research problems were solved, thereby improving the quality and effectiveness of English education. This paper analyzed and modeled the learningdata of students, and combined the advantages of LSTM algorithm to achieve personalized learning paths and guidance for different students, better meeting the learning needs and levels of different students;in order to better understand how students learn vocabulary and to offer more useful advice and support for teaching practices, the LSTM algorithm was applied. The training loss obtained by using grid search method was 0.65, and the validation loss was 0.75;the training loss obtained by the random search method was 0.7, and the validation loss was 0.85;the training loss obtained by Bayesian optimization method was 0.8, and the validation loss was 0.9;the training loss obtained by the genetic algorithm method was 0.85, and the validation loss was 1.1. The model obtained by the grid search method performed well on both the training and validation sets, with good fitting and generalization abilities.
The present study uses deep learning methods to detect autism spectrum disorder (ASD) in patients from global multi-site database Autism Brain Imaging data Exchange (ABIDE) based on brain activity patterns. ASD is a n...
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Issues of providing mental health support to people with emerging or current mental health disorders are becoming a significant concern throughout the world. One of the biggest effects of digital psychiatry during COV...
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Purpose - Building information modeling (BIM) is a striking development in the architecture, engineering and construction (AEC) industry, which provides in-depth information on different stages of the building lifecyc...
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Purpose - Building information modeling (BIM) is a striking development in the architecture, engineering and construction (AEC) industry, which provides in-depth information on different stages of the building lifecycle. Real estate valuation, as a fully interconnected field with the AEC industry, can benefit from 3D technical achievements in BIM technologies. Some studies have attempted to use BIM for real estate valuation procedures. However, there is still a limited understanding of appropriate mechanisms to utilize BIM for valuation purposes and the consequent impact that BIM can have on decreasing the existing uncertainties in the valuation methods. Therefore, the paper aims to analyze the literature on BIM for real estate valuation practices. Design/methodology/approach - This paper presents a systematic review to analyze existing utilizations of BIM for real estate valuation practices, discovers the challenges, limitations and gaps of the current applications and presents potential domains for future investigations. Research was conducted on the Web of Science, Scopus and Google Scholar databases to find relevant references that could contribute to the study. A total of 52 publications including journal papers, conference papers and proceedings, book chapters and PhD and master's theses were identified and thoroughly reviewed. There was no limitation on the starting date of research, but the end date was May 2022. Findings - Four domains of application have been identified: (1) developing machinelearning-based valuation models using the variables that could directly be captured through BIM and industry foundation classes (IFC) data instances of building objects and their attributes;(2) evaluating the capacity of 3D factors extractable from BIM and 3D GIS in increasing the accuracy of existing valuation models;(3) employing BIM for accurate estimation of components of cost approach-based valuation practices;and (4) extraction of useful visual features for rea
Climate change has led to a sharp increase in the number and severity of extreme events, such as floods, tornados and wildfires. These events have resulted in adverse effects on human lives and the infrastructure. Swi...
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ISBN:
(纸本)9798400704369
Climate change has led to a sharp increase in the number and severity of extreme events, such as floods, tornados and wildfires. These events have resulted in adverse effects on human lives and the infrastructure. Swift disaster assessment is crucial for the effective planning of disaster response and relief efforts. AI and big data have provided unprecedented opportunities to enable swift disaster assessment, but two significant hurdles exist: (1) the scarcity of annotated geospatial data to train AI models, and (2) the lack of AI solutions that encode physics knowledge in a geospatial context. My research aims to address both challenges by developing an active-learning-based annotation platform that improves the annotation productivity of geospatial data for geospatial machinelearning, and by developing physics-guided machinelearning models for accurate natural disaster assessment.
Effective illness diagnosis is an unmet clinical need on a global scale. Building a tool for early diagnosis and an efficient course of treatment is particularly challenging due to the complexity of many complex disea...
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Most of the jade on the market now comes from Myanmar, Guatemala, and a few from Russia. The gemological properties of jadeite from different producing areas are consistent. However, in the middle-end jade market, und...
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