Method Selection for Travel Forecasting

2017 ◽  
Author(s):  
Maren Outwater and Kevin Hathaway ◽  
◽  
◽  
Keyword(s):  
Method Selection ◽  
Travel Forecasting ◽  
Selection For

scholarly journals Evaporation from a large lowland reservoir – (dis)agreement between evaporation models from hourly to decadal timescales

2020 ◽  
Vol 24 (3) ◽  
pp. 1055-1072 ◽  
Author(s):  
Femke A. Jansen ◽  
Adriaan J. Teuling
Keyword(s):  
Land Surface ◽  
Positive Trend ◽  
Hydrological Models ◽  
Water Losses ◽  
Surface Evaporation ◽  
Diurnal Cycles ◽  
Method Selection ◽  
Lowland Reservoir ◽  
Selection For ◽  
Evaporation Models

Abstract. Accurate monitoring and prediction of surface evaporation become more crucial for adequate water management in a changing climate. Given the distinct differences between characteristics of a land surface and a water body, evaporation from water bodies requires a different parameterization in hydrological models. Here we compare six commonly used evaporation methods that are sensitive to different drivers of evaporation, brought about by a different choice of parameterization. We characterize the (dis)agreement between the methods at various temporal scales ranging from hourly to 10-yearly periods, and we evaluate how this reflects in differences in simulated water losses through evaporation of Lake IJssel in the Netherlands. At smaller timescales the methods correlate less (r=0.72) than at larger timescales (r=0.97). The disagreement at the hourly timescale results in distinct diurnal cycles of simulated evaporation for each method. Although the methods agree more at larger timescales (i.e. yearly and 10-yearly), there are still large differences in the projected evaporation trends, showing a positive trend to a more (i.e. Penman, De Bruin–Keijman, Makkink, and Hargreaves) or lesser extent (i.e. Granger–Hedstrom and FLake). The resulting discrepancy between the methods in simulated water losses of the Lake IJssel region due to evaporation ranges from −4 mm (Granger–Hedstrom) to −94 mm (Penman) between the methods. This difference emphasizes the importance and consequence of the evaporation method selection for water managers in their decision making.

scholarly journals Strategies of method selection for fine-scale PM<sub>2.5</sub> mapping in an intra-urban area using crowdsourced monitoring

2019 ◽  
Vol 12 (5) ◽  
pp. 2933-2948 ◽  
Author(s):  
Shan Xu ◽  
Bin Zou ◽  
Yan Lin ◽  
Xiuge Zhao ◽  
Shenxin Li ◽  
...  
Keyword(s):  
Air Pollution ◽  
Air Quality ◽  
Urban Area ◽  
Significant Risk ◽  
Pollution Monitoring ◽  
Fine Scale ◽  
Method Selection ◽  
Sampling Campaign ◽  
Selection For ◽  
Monitoring Stations

Abstract. Fine particulate matter (PM2.5) is of great concern to the public due to its significant risk to human health. Numerous methods have been developed to estimate spatial PM2.5 concentrations in unobserved locations due to the sparse number of fixed monitoring stations. Due to an increase in low-cost sensing for air pollution monitoring, crowdsourced monitoring of exposure control has been gradually introduced into cities. However, the optimal mapping method for conventional sparse fixed measurements may not be suitable for this new high-density monitoring approach. This study presents a crowdsourced sampling campaign and strategies of method selection for 100 m scale PM2.5 mapping in an intra-urban area of China. During this process, PM2.5 concentrations were measured by laser air quality monitors through a group of volunteers during two 5 h periods. Three extensively employed modelling methods (ordinary kriging, OK; land use regression, LUR; and regression kriging, RK) were adopted to evaluate the performance. An interesting finding is that PM2.5 concentrations in micro-environments varied in the intra-urban area. These local PM2.5 variations can be easily identified by crowdsourced sampling rather than national air quality monitoring stations. The selection of models for fine-scale PM2.5 concentration mapping should be adjusted according to the changing sampling and pollution circumstances. During this project, OK interpolation performs best in conditions with non-peak traffic situations during a lightly polluted period (holdout validation R2: 0.47–0.82), while the RK modelling can perform better during the heavily polluted period (0.32–0.68) and in conditions with peak traffic and relatively few sampling sites (fewer than ∼100) during the lightly polluted period (0.40–0.69). Additionally, the LUR model demonstrates limited ability in estimating PM2.5 concentrations on very fine spatial and temporal scales in this study (0.04–0.55), which challenges the traditional point about the good performance of the LUR model for air pollution mapping. This method selection strategy provides empirical evidence for the best method selection for PM2.5 mapping using crowdsourced monitoring, and this provides a promising way to reduce the exposure risks for individuals in their daily life.

METHOD SELECTION FOR STIFFENERS WELDING TO CAST PRODUCTS

2019 ◽  
Vol 18 (2) ◽  
pp. 259-266
Author(s):  
Matarneh Mohammed ◽  
Al Quran Firas ◽  
Gharaibeh Nabeel ◽  
V. V. Chigarev ◽  
A. V. Loza
Keyword(s):  
Method Selection ◽  
Selection For ◽  
Cast Products

scholarly journals PENGGUNAAN AHP UNTUK PEMILIHAN METODE PERENCANAAN ANTARA KONVENSIONAL DENGAN BIM PADA REDESIGN PROYEK KONSTRUKSI

2019 ◽  
Vol 1 (3) ◽  
pp. 263-273
Author(s):  
Iwan Supriyadi ◽  
Aland Hasbi
Keyword(s):  
Decision Making ◽  
Construction Projects ◽  
Planning Method ◽  
Field Analysis ◽  
Advantages And Disadvantages ◽  
Method Selection ◽  
Global Weight ◽  
Training Cost ◽  
Selection For ◽  
The Cost

Abstract  During the construction projects, delays usually happen which are mainly caused by reworks, where 60% of reworks are caused by design failure. Since designs have a major impact on construction projects, there are methods to correctly create a design. Three methods of planning that can be done are conventional, semi-conventional, and BIM methods. The three methods have both advantages and disadvantages. Decision making for method selection for redesigning is very crucial to avoid delays to a project. The three main criteria in method selection are cost, time, and system. This research was done to decide the main criteria, sub-criteria, and an alternative in decision making of method selection for redesigning through the use of AHP (Analytical Hierarchy Process) and analyze conditions on the field with the result of AHP analysis. The result showed that cost was the main criterion with a weight if 0.40 and the sub-criterion for the cost was the HR  training cost with a global weight of 0.21. Alternative planning method selected was the BIM method with a global weight of 0.66. The result of field analysis showed that BIM planning method was 60.4% faster than the conventional method with an increase of training cost by 62.5%. The conclusion of this research was that BIM planning method was more efficient than conventional and semi-conventional planning in the process of re-design.Key words: Re-design, Conventional, BIM, AHPAbstrak Pada pelaksanaan proyek konstruksi, keterlambatan dengan rework menjadi penyebab utama dimana 60% penyebab Rework disebabkan oleh kesalahan desain. Besarnya dampak desain pada proyek konstruksi maka berbagai cara dilakukan untuk menyelesaikan proses desain dengan tepat. Tiga metode perencanaan yang dapat dilakukan yaitu Metode Konvensional, Metode Semi Konvensional, dan Metode BIM. Ketiga metode perencanaan tersebut sama-sama memiliki kelebihan dan kekurangan. Pengambilan keputusan saat pemilihan metode perencanaan pada pekerjaan re-design sangat krusial dalam mengurangi keterlambatan proyek. Banyaknya variabel dan kurangnya kriteria obyektif menyulitkan proses pemilihan metode perencanaan re-design. Tiga kriteria utama dalam proses pengambilan keputusan dalam pemilihan metode perencanaan re-design yaitu biaya, waktu, sistem. Penelitian ini dilakukan untuk menentukan kriteria utama, subkriteria dan alternatif dalam penentuan pengambilan keputusan dalam pemilihan metode perencanaan re-design dengan menggunakan metode AHP (Analytical Hirerachy Process) dan menganalisa kondisi di lapangan dengan hasil analisis AHP. Hasil penelitian menunjukkan biaya menjadi kriteria utama dengan bobot sebesar 0.40 dan subkriteria yang terpilih adalah biaya pelatihan SDM dengan bobot global sebesar 0.21. Alternatif metode perencanaan yang dipilih adalah metode perencanaan BIM dengan bobot global sebesar 0.66. Hasil analisis lapangan juga menunjukan bahwa metode perencanaan BIM lebih cepat 60.4% dari metode perencanaan konvensional dengan peningkatan biaya pelatihan sebesar 62.5%. Simpulan dari penelitian ini adalah Metode Perencanaan BIM lebih efisien daripada Perencanaan Konvensional maupun semi-konvensional dalam pengerjaan re-design.Kata kunsi : Re-design, Konvensional, BIM, AHP

scholarly journals Analytical Method Selection for Drug Product Dissolution Testing

2006 ◽  
Vol 13 (3) ◽  
pp. 6-13 ◽  
Author(s):  
Qingxi Wang ◽  
Decheng Ma ◽  
John P. Higgins
Keyword(s):  
Analytical Method ◽  
Drug Product ◽  
Dissolution Testing ◽  
Method Selection ◽  
Selection For

scholarly journals Strategies of Method Selection for Fine Scale PM<sub>2.5</sub> Mapping in Intra-Urban Area Under Crowdsourcing Monitoring

2019 ◽  
Author(s):  
Shan Xu ◽  
Bin Zou ◽  
Yan Lin ◽  
Xiuge Zhao ◽  
Shenxin Li ◽  
...  
Keyword(s):  
Urban Area ◽  
Significant Risk ◽  
Mapping Method ◽  
Pollution Monitoring ◽  
Selection Strategy ◽  
Air Pollution Monitoring ◽  
Method Selection ◽  
Period 2 ◽  
Sampling Campaign ◽  
Selection For

Abstract. Fine particulate matters (PM2.5) are of great concern to public due to their significant risk to human health. Numerous methods have been developed to estimate spatial PM2.5 concentrations at unobserved locations due to the sparse fixed monitoring stations. On the other hand, as the rising of low-cost sensing for air pollution monitoring, crowdsourcing activities has been gradually introduced into fine exposure control in cities. However, the optimal mapping method for conventional sparse fixed measurements may not suit this new high-density monitoring way. This study therefore for the first time presents a crowdsourcing sampling campaign and strategies of method selection for hundred meter-scale level PM2.5 mapping in intra-urban area of China. In this process, the crowdsourcing sampling campaign was developed through a group of volunteers and their smart phone applications; the best performed mapping approach was chosen by comparing three widely used modelling method (ordinary kriging (OK), land use regression (LUR), and universal kriging combined OK and LUR (UK)) with increasing training sites. Results show that crowdsourcing based PM2.5 measurements varied significantly by sites (i.e. urban microenvironments) (Period 1: 28–136 µg m−3; Period 2: 115–266 µg m−3) and clearly differed from those at national monitoring sites (Period 1: 20–58 µg m−3; Period 2: 146–219 µg m−3). Despite the performance of the three models in estimating PM2.5 concentrations all improved as the number of training sites increase, OK interpolation performed best under conditions with non-peak traffic (9:00–11:00) in Period 1 (i.e. light-polluted period) with the hold-out validation R2 ranging from 0.47 to 0.82. Meanwhile, the accuracy of UK was the highest for 8:00 and 12:00 with less than 70 % training sites (0.40–0.69) and all five hours of Period 2 (i.e. heavy-polluted period) (0.32–0.68). Comparatively, LUR demonstrated limited ability in PM2.5 concentration simulations (0.04–0.55). Moreover, spatial distributions of PM2.5 concentrations based on the selected model with crowdsourcing data clearly illustrated their hourly intra urban variations which are generally concealed by the results from national air quality monitoring sites. This method selection strategy provides solid experimental evidence for method selection of PM2.5 mapping under crowdsourcing monitoring and a promising access to the prevention of exposure risks for individuals in their daily life.

scholarly journals Enhanced Oil Recovery Method Selection for Shale Oil Based on Numerical Simulations

ACS Omega ◽  
2021 ◽  
Author(s):  
Elena Mukhina ◽  
Alexander Cheremisin ◽  
Lyudmila Khakimova ◽  
Alsu Garipova ◽  
Ekaterina Dvoretskaya ◽  
...  
Keyword(s):  
Numerical Simulations ◽  
Enhanced Oil Recovery ◽  
Oil Recovery ◽  
Shale Oil ◽  
Recovery Method ◽  
Method Selection ◽  
Selection For
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