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    Findings from Newcastle University Update Knowledge of Machine Learning (A Unifi ed Cross-series Marine Propeller Design Method Based On Machine Learning)

    69-70页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Researchers detail new data in Machine Learning. According to news reporting fromNewcastle upon Tyne, United Kingdom, by NewsRx journalists, research stated, “Propeller design diagrams,like Bp-del ta diagram, are widely applied in ship propeller design. However, different prop eller series usevarious selection approaches, so comparisons between designs ar e only possible after individual candidatesare chosen.”

    Findings from Newcastle University Update Knowledge of Machine Learning (A Unifi ed Cross-series Marine Propeller Design Method Based On Machine Learning)

    69-70页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Researchers detail new data in Machine Learning. According to news reporting fromNewcastle upon Tyne, United Kingdom, by NewsRx journalists, research stated, “Propeller design diagrams,like Bp-del ta diagram, are widely applied in ship propeller design. However, different prop eller series usevarious selection approaches, so comparisons between designs ar e only possible after individual candidatesare chosen.”

    Researchers at University of Nottingham Report New Data on Machine Learning [Investigation of a Model Predictive Control (Mpc) Strategy for Seasonal Thermoch emical Energy Storage Systems In District Heating Networks]

    70-71页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - A new study on Machine Learning is now available. According to news reportingoriginating from Nottingham, United King dom, by NewsRx correspondents, research stated, “This researchinvestigates the integration of model predictive control (MPC) with seasonal thermochemical energ ystorage systems (STES) within district heating networks, focusing on the Notti ngham district heating asa case study. The primary aim is to develop an MPC str ategy that utilizes machine learning models foraccurate heat load forecasting.”

    Researchers at University of Nottingham Report New Data on Machine Learning [Investigation of a Model Predictive Control (Mpc) Strategy for Seasonal Thermoch emical Energy Storage Systems In District Heating Networks]

    70-71页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - A new study on Machine Learning is now available. According to news reportingoriginating from Nottingham, United King dom, by NewsRx correspondents, research stated, “This researchinvestigates the integration of model predictive control (MPC) with seasonal thermochemical energ ystorage systems (STES) within district heating networks, focusing on the Notti ngham district heating asa case study. The primary aim is to develop an MPC str ategy that utilizes machine learning models foraccurate heat load forecasting.”

    Investigators at Brunel University London Detail Findings in Machine Learning (F orecasting Digital Asset Return: an Application of Machine Learning Model)

    71-72页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Data detailed on Machine Learning have been presented. According to news reportingout of Uxbridge, United Kingdom, by NewsRx editors, research stated, “In this study, we aim to identify themachine learning model that can overcome the limitations of traditional statistical mod elling techniquesin forecasting Bitcoin prices. Also, we outline the necessary conditions that make the model suitable.”Our news journalists obtained a quote from the research from Brunel University L ondon, “We drawon a multivariate large data set of Bitcoin prices and its marke t microstructure variables and apply threemachine learning models, namely doubl e deep Q-learning, XGBoost and ARFIMA-GARCH. The findingsshow that the double d eep Q-learning model outperforms the others in terms of returns and Sortino ratio and is capable of one-step-ahead sign forecast of the returns even on syntheti c data.”

    Investigators at Brunel University London Detail Findings in Machine Learning (F orecasting Digital Asset Return: an Application of Machine Learning Model)

    71-72页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Data detailed on Machine Learning have been presented. According to news reportingout of Uxbridge, United Kingdom, by NewsRx editors, research stated, “In this study, we aim to identify themachine learning model that can overcome the limitations of traditional statistical mod elling techniquesin forecasting Bitcoin prices. Also, we outline the necessary conditions that make the model suitable.”Our news journalists obtained a quote from the research from Brunel University L ondon, “We drawon a multivariate large data set of Bitcoin prices and its marke t microstructure variables and apply threemachine learning models, namely doubl e deep Q-learning, XGBoost and ARFIMA-GARCH. The findingsshow that the double d eep Q-learning model outperforms the others in terms of returns and Sortino ratio and is capable of one-step-ahead sign forecast of the returns even on syntheti c data.”

    Study Results from Xi’an University of Technology Update Understanding of Machin e Learning (Drought Characteristics Prediction Using a Hybrid Machine Learning M odel With Correction)

    72-73页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Data detailed on Machine Learning have been presented. According to news reporting originating in Shaanxi, People’s Re public of China, by NewsRx journalists, research stated, “Droughtprediction is a crucial aspect of drought risk assessment, playing a significant role in effec tively minimizinglosses associated with droughts. While many previous studies h ave focused on the variations of droughtindices, understanding the impact of dr ought events requires a transformation into drought characteristicssuch as seve rity and duration.”

    Study Results from Xi’an University of Technology Update Understanding of Machin e Learning (Drought Characteristics Prediction Using a Hybrid Machine Learning M odel With Correction)

    72-73页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Data detailed on Machine Learning have been presented. According to news reporting originating in Shaanxi, People’s Re public of China, by NewsRx journalists, research stated, “Droughtprediction is a crucial aspect of drought risk assessment, playing a significant role in effec tively minimizinglosses associated with droughts. While many previous studies h ave focused on the variations of droughtindices, understanding the impact of dr ought events requires a transformation into drought characteristicssuch as seve rity and duration.”

    Researchers from BRAC University Publish New Studies and Findings in the Area of Machine Learning (Climate data dynamics: A high-volume real world structured we ather datasetMendeley Data)

    72-72页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Investigators publish new report on ar tificial intelligence. According to news reportingoriginating from Dhaka, Bangl adesh, by NewsRx correspondents, research stated, “The dataset at hand is auniq ue resource, officially procured from the Bangladesh Meteorological Department, the sole governmentinstitution that diligently monitors weather through 35 stra tegically placed weather stations across thenation.”

    Researchers from BRAC University Publish New Studies and Findings in the Area of Machine Learning (Climate data dynamics: A high-volume real world structured we ather datasetMendeley Data)

    72-72页
    查看更多>>摘要:By a News Reporter-Staff News Editor at Robotics & Machine Learning DailyNews Daily News - Investigators publish new report on ar tificial intelligence. According to news reportingoriginating from Dhaka, Bangl adesh, by NewsRx correspondents, research stated, “The dataset at hand is auniq ue resource, officially procured from the Bangladesh Meteorological Department, the sole governmentinstitution that diligently monitors weather through 35 stra tegically placed weather stations across thenation.”