scholarly journals A cost prediction model for machine operation in multi-field production systems

2016 ◽  
Vol 73 (5) ◽  
pp. 397-405 ◽  
Author(s):  
Alessandro Sopegno ◽  
Patrizia Busato ◽  
Remigio Berruto ◽  
Thiago Libório Romanelli
Author(s):  
Yang Fang ◽  
Gerardo H. Nunez ◽  
Mariana Neves da Silva ◽  
Douglas A. Phillips ◽  
Patricio R. Munoz

Southern highbush blueberry plantations have been expanded into worldwide non-traditional growing areas with elite cultivars and improved horticultural practices. This article presents a comprehensive review of current production systems – alternatives to traditional open field production – such as production in protected environments, high-density plantings, evergreen production, and container-based production. We discuss the advantages and disadvantages of each system and compare their differences to the open field production. In addition, potential solutions have been provided for some of the disadvantages. We also highlight some of the gaps existing between academic studies and production in industry, providing a guide for future academic research. All these alternative systems have shown the potential to produce high yields with high quality berries. Alternative systems, compared to the field production, require higher establishment investments and thus create an entry barrier for new producers. Nevertheless, with their advantages, alternative productions have potential to be profitable.


2019 ◽  
Vol 258 ◽  
pp. 02027
Author(s):  
Hirijanto ◽  
I Wayan Mundra ◽  
Addy Utomo

Project’s cost is one of important components in project achievement. Because of the uniqueness of construction projects, cost estimation always differs from project to project. The rate of cost components always change over time make difficult to forecast the cost for the upcoming project. The cost component consists of many influencing variables where there is interrelationship each other affecting to the total project cost. This paper objective is to develop a cost prediction model to assist the project planners in cost estimation for future projects. System dynamic is one of the appropriate methods to analyse system behaviour with interrelationship referring to the historic data, so it is able to predict the future project. Developing the model, primary and secondary data are collected from previous studies, interview with the government planner and survey in Malang Regency. The model simulation is Brick work unit with its components. Data from last thirteen years are used to verify and validate the developed model by causal loop diagram as a basic method in system dynamic. The finding showed that the model is closed to real condition through the validation mechanism. The developed system is useful in decision making of budget planning based on work quantity.


Symmetry ◽  
2020 ◽  
Vol 12 (8) ◽  
pp. 1352
Author(s):  
Suhui Wang ◽  
Fei-Fei Ye

In order to solve the problem of environmental governance investment planning in the transportation industry, a cost prediction model is proposed under technological constraints, where the input output indictors emphasizes the flexibility of prediction and its characters are asymmetric, while the constructs of prediction model focuses on the standardization and its characters are symmetrical. The basic principle of the cost prediction model is based on an extended belief rule-based (EBRB) system to model the input-output relationship in investment planning, and a parameter learning model to improve the accuracy of the EBRB system. Additionally, the technological innovation factors are also embedded in the cost prediction model to investigate the influence of technology-related outcomes on investment planning. Finally, based on the data of environmental governance in China’s transportation industry from 2003 to 2016, the cost of transportation industry environmental management in China’s thirty provinces from 2017 to 2033 is predicted under the constraints of technological innovation. Results show that: (1) the accuracy of the proposed cost prediction model is higher than some existing cost prediction methods; (2) the predicted environmental governance costs have a significant regional difference; (3) the upgrading of technological innovation is conducive to saving the future environmental governance costs of the transportation industry in some provinces. In addition to the above results, the present study provides model supports and policy references for government decision makers in transportation industry-related environmental cost planning.


2019 ◽  
Vol 59 ◽  
pp. 291-296 ◽  
Author(s):  
Xugang Zhang ◽  
Xiuyi Ao ◽  
Zhigang Jiang ◽  
Hua Zhang ◽  
Wei Cai

2021 ◽  
Vol ahead-of-print (ahead-of-print) ◽  
Author(s):  
Miao Fan ◽  
Ashutosh Sharma

PurposeIn order to improve the accuracy of project cost prediction, considering the limitations of existing models, the construction cost prediction model based on SVM (Standard Support Vector Machine) and LSSVM (Least Squares Support Vector Machine) is put forward.Design/methodology/approachIn the competitive growth and industries 4.0, the prediction in the cost plays a key role.FindingsAt the same time, the original data is dimensionality reduced. The processed data are imported into the SVM and LSSVM models for training and prediction respectively, and the prediction results are compared and analyzed and a more reasonable prediction model is selected.Originality/valueThe prediction result is further optimized by parameter optimization. The relative error of the prediction model is within 7%, and the prediction accuracy is high and the result is stable.


2012 ◽  
Vol 22 (5) ◽  
pp. 659-668 ◽  
Author(s):  
Russell W. Wallace ◽  
Annette L. Wszelaki ◽  
Carol A. Miles ◽  
Jeremy S. Cowan ◽  
Jeffrey Martin ◽  
...  

Field studies were conducted during 2010 and 2011 in Knoxville, TN; Lubbock, TX; and Mount Vernon, WA; to compare high tunnel and open-field organic production systems for season extension and adverse climate protection on lettuce (Lactuca sativa) yield and quality. The climates of these locations are diverse and can be typified as hot and humid (Knoxville), hot and dry (Lubbock), and cool and humid (Mount Vernon). In both years, 6-week-old lettuce seedlings of ‘New Red Fire’ and ‘Green Star’ (leafy type), ‘Adriana’ and ‘Ermosa’ (butterhead type), and ‘Coastal Star’ and ‘Jericho’ (romaine type) were transplanted in the late winter or early spring into subplots covered with black plastic and grown to maturity (43 to 65 days). Lettuce harvest in Knoxville occurred at 50 to 62 days after transplanting (DAT), with open-field lettuce harvested an average of 9 days earlier compared with high tunnel plots both years (P > 0.0001). The earlier than anticipated harvests in the open-field in Knoxville in 2010 were due to lettuce bolting. In Lubbock, high tunnel lettuce was harvested an average 16 days earlier in 2010 compared with open-field lettuce (P > 0.0001), while in 2011, high temperatures and bolting required that open-field lettuce be harvested 4 days earlier than lettuce grown in high tunnels. On average, lettuce cultivars at Mount Vernon matured and were harvested 56 to 61 DAT in 2010 and 54 to 64 DAT in 2011 with no significant differences between high tunnel and open-field production systems. Total and marketable yields at Mount Vernon and Lubbock averaged across cultivars were comparable in both high tunnel and open-field plots. At Knoxville, although total yields were significantly higher (P > 0.0062) in high tunnels than open-field plots, incidence of insect, disease, and physiological damage in high tunnel plots reduced lettuce quality and marketable yield (P > 0.0002). Lettuce head length:diameter ratio (LDR) averaged across cultivars was equal between high tunnel and the open field at all three locations. High tunnel production systems offer greater control of environments suitable for lettuce production, especially in climates like Knoxville and Lubbock where later-planted open-field systems may be more susceptible to temperature swings that may affect lettuce quality. These results suggest that although high tunnel culture alone may influence lettuce yield and quality, regional climates likely play a critical role in determining the impact of these two production systems on marketable lettuce yields.


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