Deformation Monitoring and Forecasting Model Study Based on Grey System Theory

The grey system theory studies the uncertainty of small sample size problems. This paper using grey system theory in the deformation monitoring field, based on analysis of present grey forecast models, developed the spatial multi-point model. By using residual modification, the spatial multi-point residual model eras developed in further study. Then, combined with the sedimentation data of Xiaolangdi Multipurpose Dam, the results are compared and analyzed, the conclusion has been made and the advantages of the residual spatial multi-point model has been proved.

Application of forecasting structural cracks technique of 3D move in Chengdao buried hill

3DMove software, based on the three-dimension structural model of geologic interpretation, can forecast reservoir cracks from the point of view of formation of the structural geology, and analyze the characteristics of the cracks. 3DMove software dominates in forecasting cracks. We forecast the developments and directions of the cracks in Chengbei buried hill with the application of forecasting technique in 3DMove software, and obtain the chart about strain distributing on top in buried hill and the chart about relative density and orientation and the chart about the analysis of crack unsealing. In Chengbei 30 buried hill zone, north-west and north-east and approximately east-west cracks in Cenozoic are very rich and the main directions in every fault block are different. Forecasting results that are also verified by those of drilling approximately accord with the data from well logging, the case of which shows that the technique has the better ability in forecasting cracks, and takes more effects on exploration and exploitation of crack reservoir beds in ancient buried hill reservoirs.

Heritage interpretation challenges and management issues at film-induced tourism heritage attractions: Case studies of Rosslyn Chapel and Alnwick Castle

Although previous research has widely acknowledged the phenomenon of film-induced tourism, there is a paucity of research in relation to management of film-induced tourism at built heritage sites. This research, underpinned by a constructivist paradigm, draws on three distinct fields of study – heritage tourism management, film-induced tourism and heritage interpretation – in order to provide a contribution to the heritage management field and address this particular gap in knowledge. Relying on the method of semi-structured interviews with managers, guides and visitors at Rosslyn Chapel (RC) and Alnwick Castle (AC), this thesis provides a rich understanding of how heritage interpretation can address a range of management challenges at heritage sites where film-induced tourism has occurred. These heritage visitor attractions (HVAs) were specifically selected as case studies as they have played different roles in media products. Rosslyn Chapel (RC) was an actual place named in The Da Vinci Code (TDVC) book and then film, whereas Alnwick Castle (AC) served as a backdrop for the first two Harry Potter (HP) films. Findings of this research include a range of management challenges at both RC and AC such as an increase in visitor numbers; seasonality issues; changes in visitor profile; revenue generation concerns; conservation, access, and visitor experience; and the complex relationship between heritage management and tourism activities. The findings also reveal film-induced tourism’s implications for heritage interpretation such as the various visitors’ expectations for heritage interpretation, changes to heritage interpretation as a result of film-induced tourism, and issues with commodification. These findings also demonstrate that film-induced tourism to some extent influenced visitors’ preferences for heritage interpretation, though visitors’ preferences differed from one to another. This thesis argues that, in the context of film-induced tourism at HVAs, as evident from the two case studies considered, heritage interpretation can be a valuable management tool and can also play a significant role in the quality of the visitors’ experience.

Is China's fifth-largest inland lake to dry-up? Incorporated hydrological and satellite-based methods for forecasting Hulun Lake water levels

Hulun Lake, China’s fifth-largest inland lake, experienced severe declines in water level in the period of 2000-2010. This has prompted concerns whether the lake is drying up gradually. A multi-million US dollar engineering project to construct a water channel to transfer part of the river flow from a nearby river to maintain the water level was completed in August 2010. This study aimed to advance the understanding of the key processes controlling the lake water level variation over the last five decades, as well as investigate the impact of the river transfer engineering project on the water level. A water balance model was developed to investigate the lake water level variations over the last five decades, using hydrological and climatic data as well as satellite-based measurements and results from land surface modelling. The investigation reveals that the severe reduction of river discharge (- 364±64 mm/yr, ~70% of the five-decade average) into the lake was the key factor behind the decline of the lake water level between 2000 and 2010. The decline of river discharge was due to the reduction of total runoff from the lake watershed. This was a result of the reduction of soil moisture due to the decrease of precipitation (-49±45 mm/yr) over this period. The water budget calculation suggests that the groundwater component from the surrounding lake area as well as surface run off from the un-gauged area surrounding the lake contributed ~ net 210 Mm3/yr (equivalent to ~ 100 mm/yr) water inflows into the lake. The results also show that the water diversion project did prevent a further water level decline of over 0.5 m by the end of 2012. Overall, the monthly water balance model gave an excellent prediction of the lake water level fluctuation over the last five decades and can be a useful tool to manage lake water resources in the future.

Re-conceptualising rural resources as countryside capital: The case of rural tourism

Brian Garrod, Roz Wornell and Ray Youell (2006). Re-conceptualising rural resources as countryside capital: The case of rural tourism. Journal of Rural Studies, 22 (1), 117-128. RAE2008

Uncertainty in wind energy forecasting

Wind energy is the energy source that contributes most to the renewable energy mix of European countries. While there are good wind resources throughout Europe, the intermittency of the wind represents a major problem for the deployment of wind energy into the electricity networks. To ensure grid security a Transmission System Operator needs today for each kilowatt of wind energy either an equal amount of spinning reserve or a forecasting system that can predict the amount of energy that will be produced from wind over a period of 1 to 48 hours. In the range from 5m/s to 15m/s a wind turbine’s production increases with a power of three. For this reason, a Transmission System Operator requires an accuracy for wind speed forecasts of 1m/s in this wind speed range. Forecasting wind energy with a numerical weather prediction model in this context builds the background of this work. The author’s goal was to present a pragmatic solution to this specific problem in the ”real world”. This work therefore has to be seen in a technical context and hence does not provide nor intends to provide a general overview of the benefits and drawbacks of wind energy as a renewable energy source. In the first part of this work the accuracy requirements of the energy sector for wind speed predictions from numerical weather prediction models are described and analysed. A unique set of numerical experiments has been carried out in collaboration with the Danish Meteorological Institute to investigate the forecast quality of an operational numerical weather prediction model for this purpose. The results of this investigation revealed that the accuracy requirements for wind speed and wind power forecasts from today’s numerical weather prediction models can only be met at certain times. This means that the uncertainty of the forecast quality becomes a parameter that is as important as the wind speed and wind power itself. To quantify the uncertainty of a forecast valid for tomorrow requires an ensemble of forecasts. In the second part of this work such an ensemble of forecasts was designed and verified for its ability to quantify the forecast error. This was accomplished by correlating the measured error and the forecasted uncertainty on area integrated wind speed and wind power in Denmark and Ireland. A correlation of 93% was achieved in these areas. This method cannot solve the accuracy requirements of the energy sector. By knowing the uncertainty of the forecasts, the focus can however be put on the accuracy requirements at times when it is possible to accurately predict the weather. Thus, this result presents a major step forward in making wind energy a compatible energy source in the future.

Current methods and advances in forecasting of wind power generation

Wind power generation differs from conventional thermal generation due to the stochastic nature of wind. Thus wind power forecasting plays a key role in dealing with the challenges of balancing supply and demand in any electricity system, given the uncertainty associated with the wind farm power output. Accurate wind power forecasting reduces the need for additional balancing energy and reserve power to integrate wind power. Wind power forecasting tools enable better dispatch, scheduling and unit commitment of thermal generators, hydro plant and energy storage plant and more competitive market trading as wind power ramps up and down on the grid. This paper presents an in-depth review of the current methods and advances in wind power forecasting and prediction. Firstly, numerical wind prediction methods from global to local scales, ensemble forecasting, upscaling and downscaling processes are discussed. Next the statistical and machine learning approach methods are detailed. Then the techniques used for benchmarking and uncertainty analysis of forecasts are overviewed, and the performance of various approaches over different forecast time horizons is examined. Finally, current research activities, challenges and potential future developments are appraised.

Power system parameters forecasting using Hilbert-Huang transform and machine learning

A novel hybrid data-driven approach is developed for forecasting power system parameters with the goal of increasing the efficiency of short-term forecasting studies for non-stationary time-series. The proposed approach is based on mode decomposition and a feature analysis of initial retrospective data using the Hilbert-Huang transform and machine learning algorithms. The random forests and gradient boosting trees learning techniques were examined. The decision tree techniques were used to rank the importance of variables employed in the forecasting models. The Mean Decrease Gini index is employed as an impurity function. The resulting hybrid forecasting models employ the radial basis function neural network and support vector regression. A part from introduction and references the paper is organized as follows. The second section presents the background and the review of several approaches for short-term forecasting of power system parameters. In the third section a hybrid machine learningbased algorithm using Hilbert-Huang transform is developed for short-term forecasting of power system parameters. Fourth section describes the decision tree learning algorithms used for the issue of variables importance. Finally in section six the experimental results in the following electric power problems are presented: active power flow forecasting, electricity price forecasting and for the wind speed and direction forecasting.

Social tourism today: Stakeholders, and supply and demand factors

As highlighted in the previous chapter, the definitions and consequently the expression of social tourism have developed and changed since its inception in the 19th century. In post-modern times there has been a significant evolution of the needs, the expectations and the possibilities (or opportunities) for holidaymaking and travel in general for the majority of people in Europe. Socio-political, economic and technological developments have forged a new context for tourism and created new travel opportunities (see Chapter 6). While the numbers of tourism trips have grown steadily over time, tourism participation levels in Europe have largely stabilised: there are still a number of groups in contemporary society who are excluded from tourism. Social tourism has adapted to societal changes and has changed its focus from factory workers and manual labourers towards the current main four target groups.

Tourism is it the ‘new’ driver for regeneration?

Article explores how tourism might be the key driver to urban regeneration in towns and cities as economic crisis deepens.

Sustainability and local tourism branding in England's South Downs

This paper reports on a stakeholder consultation exercise that examined the tourism industry's perception of developing a local tourism branding scheme within the South Downs' protected areas in south-east England. The research shows that such schemes could offer potential benefits that are recognisable by the tourism industry, while helping to meet the statutory aims of the protected area. The paper records the perceptions of small tourism businesses, their fears, awareness of tourism impacts, perceptions of sustainable tourism and of local branding, and key criteria connected to the future organisation of a local tourism branding scheme. The conclusion lists the recommendations for the implementation of a local branding scheme, including grassroots stakeholder consultation that encourages ownership and participation, institutional frameworks that support capacity-building and the importance of developing core values within a local brand.