00838nam0-2200289 --450 991031935580332120190515150358.0047197925220190515d1999----kmuy0itay5050 baengGB 001yyAcidic and basic reagentsedited by Hans J. Reich and James H. RigbyChichester [etc.]Wiley©1999XII, 494 p.ill.29 cm.Handbook of reagents for organic synthesis[3]Composti organiciSintesi547.220Reich,H. J.Rigby,James H.ITUNINAREICATUNIMARCBK991031935580332180 XII B 23.39432FFABCFFABCAcidic and basic reagents879385UNINA05145nam 2201345z- 450 991074327470332120230911(CKB)5690000000228561(oapen)doab113879(EXLCZ)99569000000022856120230920c2023uuuu -u- -engurmn|---annantxtrdacontentcrdamediacrrdacarrierAdvances in Transportation MeteorologyMDPI - Multidisciplinary Digital Publishing Institute20231 online resource (304 p.)3-0365-8460-9 Transportation is one of the most crucial aspects across the world, supporting the daily life of human beings and the sustainable development of the whole of society. Generally, meteorology causes various impacts on transportation operation, safety and efficiency. In the context of global warming, increasing numbers of extreme weather and climate events (such as fog, icy roads, and extreme winds) have been detected worldwide and are expected to occur more frequently in the future. Meanwhile, extreme events, such as dense fog, rainstorm, and blizzard, tend to damage transportation and traffic facilities (such as express ways, port, airport, and high-speed railway) and induce serious traffic blocks and accidents. In recent decades, concentrated and continuous efforts have been made to carry out meteorological analyses regardless of urban traffic or transportation conditions, including those of highways, shipping, aviation, etc. A number of methods and techniques have been intensively developed to promote the qualities of both observations and forecasts. More recently, state-of-the-art machine learning frameworks have also been widely introduced into studies regarding transportation meteorology and many other fields.History of engineering and technologybicsscTechnology: general issuesbicsscTransport technology and tradesbicsscactivity densityagglomerate fogair pollutionair qualityattention mechanismsBayesian optimizationbehavioral habitsBeijing-Tianjin-Hebei regionbiasBiLSTMbuilt environmentchange characteristicsChinacivil aviation safetyclimate changeclimatologyConvLSTMCRITIC weight assignment methoddeep learningdistributiondynamic ensemble selectionearly warningEast Asiaensemble learning classifierserror decompositionexpresswayforecastforecast validationfrequencyfuzzy analytic hierarchy processgeographical factorsgo-aroundhigh-speed railwayhighwaysland use mixlow-level wind shearmachine learningmarginal seameteorological conditionsmicrowave radiometer datanowcastingobservationobservation datapavement temperaturepavement temperature predictionphone signaling datapilot reportspopulation distributionprecipitation durationprecipitation forecastPredRNNQinling mountainsrail breakagerainfallrelative humidityreviewrisk level prediction of fog-related accidentsroad blockageroad hidden dangersroad network vulnerabilitysea iceself-paced ensemblesequenceShapley additive explanationsSHapley Additive exPlanationsSiberian highspatial correlationspatial lag modelspatiotemporal distributionteleconnectiontemperaturetime-series modelingtotal rainfalltraffic flow conditionstraffic vitalitytransportation meteorologyurban meteorologyvariation characteristicsvertical distributionvisibilitywind forecastwind shearwinter icingYellow Sea and Bohai SeaHistory of engineering and technologyTechnology: general issuesTransport technology and tradesBOOK9910743274703321Advances in Transportation Meteorology3560545UNINA