統計モデルとニューラルネットワークを用いた時序列の予測研究

富山大学・富理工博甲第119号・虞瑩・2017/03/23富山大学201

一帯一路に基づく観光予測ハイブリッドモデルの研究

富山大学・富理工博甲第180号・鄭舒心・2020/9/28富山大学202

Sri Lanka – the wonder of Asia: analyzing monthly tourist arrivals in the post-war era

Using the monthly time series data, ranging over the period June 2009 to December 2018, the study applied the generalized Box-Jenkins SARIMA approach in an attempt to model and forecast international tourist arrivals in Sri Lanka.The ADF tests indicate that the tourism series is I (1). The study identified the minimum MAPE value and subsequently presented the SARIMA (0, 1, 1)(0, 1, 1)12 model as the optimal model to forecast tourist arrivals in Sri Lanka. Analysis of the residuals of the SARIMA (0, 1, 1)(0, 1, 1)12 model indicate that the selected model is stable and acceptable for forecasting tourism demand in Sri Lanka. The forecasted international tourist arrivals over the period January 2019 to December 2020 show a generally upward trend.In order to accommodate the forecasted growing numbers of international tourists, there is need for the construction of more infrastructure facilities

Application of the fruit fly optimization algorithm to an optimized neural network model in radar target recognition

With the development of computer technology, there are more and more algorithms and models for data processing and analysis, which brings a new direction to radar target recognition. This study mainly analyzed the recognition of high resolution range profile (HRRP) in radar target recognition and applied the generalized regression neural network (GRNN) model for HRRP recognition. In order to improve the performance of HRRP, the fruit fly optimization algorithm (FOA) algorithm was improved to optimize the parameters of the GRNN model. Simulation experiments were carried out on three types of aircraft. The improved FOA-GRNN (IFOA-GRNN) model was compared with the radial basis function (RBF) and GRNN models. The results showed that the IFOA-GRNN model had a better convergence accuracy, the highest average recognition rate (96.4 %), the shortest average calculation time (275 s), and a good recognition rate under noise in-terference. The experimental results show that the IFOA-GRNN model has a good performance in radar target recognition and can be further promoted and applied in practice

Conversational artificial intelligence in the AEC industry: A review of present status, challenges and opportunities

The idea of developing a system that can converse and understand human languages has been around since the 1200 s. With the advancement in artificial intelligence (AI), Conversational AI came of age in 2010 with the launch of Apple’s Siri. Conversational AI systems leveraged Natural Language Processing (NLP) to understand and converse with humans via speech and text. These systems have been deployed in sectors such as aviation, tourism, and healthcare. However, the application of Conversational AI in the architecture engineering and construction (AEC) industry is lagging, and little is known about the state of research on Conversational AI. Thus, this study presents a systematic review of Conversational AI in the AEC industry to provide insights into the current development and conducted a Focus Group Discussion to highlight challenges and validate areas of opportunities. The findings reveal that Conversational AI applications hold immense benefits for the AEC industry, but it is currently underexplored. The major challenges for the under exploration were highlighted and discusses for intervention. Lastly, opportunities and future research directions of Conversational AI are projected and validated which would improve the productivity and efficiency of the industry. This study presents the status quo of a fast-emerging research area and serves as the first attempt in the AEC field. Its findings would provide insights into the new field which be of benefit to researchers and stakeholders in the AEC industry

Conversational artificial intelligence in the AEC industry: A review of present status, challenges and opportunities

The idea of developing a system that can converse and understand human languages has been around since the 1200 s. With the advancement in artificial intelligence (AI), Conversational AI came of age in 2010 with the launch of Apple’s Siri. Conversational AI systems leveraged Natural Language Processing (NLP) to understand and converse with humans via speech and text. These systems have been deployed in sectors such as aviation, tourism, and healthcare. However, the application of Conversational AI in the architecture engineering and construction (AEC) industry is lagging, and little is known about the state of research on Conversational AI. Thus, this study presents a systematic review of Conversational AI in the AEC industry to provide insights into the current development and conducted a Focus Group Discussion to highlight challenges and validate areas of opportunities. The findings reveal that Conversational AI applications hold immense benefits for the AEC industry, but it is currently underexplored. The major challenges for the under exploration were highlighted and discusses for intervention. Lastly, opportunities and future research directions of Conversational AI are projected and validated which would improve the productivity and efficiency of the industry. This study presents the status quo of a fast-emerging research area and serves as the first attempt in the AEC field. Its findings would provide insights into the new field which be of benefit to researchers and stakeholders in the AEC industry

Theoretical Insight in Financial Decision and Brain as Fractal Computer Architecture

The purpose of this paper is to examine the theoretical interaction of brain dynamics using fractal information tools, fractal geometry in fnancial decision making. This paper concludes a scientific analytical observatory focusing on financial decision making. Through the integration of neuroscien-tific approach to the brain as a fractal and financial decision-making with the concept of fractal fi-nancial market, we open the analytical framework through two interrelated approaches that can in-crease information on making financial decisions and improve effective financial decisions in times of uncertainty. In order to achieve the aim of the work, the concept of “organized business forms” and the analogue of neurons in the financial market is the fractal – the price of a financial asset, to summarize theoretical basics, multifraktal and financial market / fractal trading, fractal computing architecture. Time series of property prices are dental lines, Fractal Computing Architectur

Advances in Public Transport Platform for the Development of Sustainability Cities

Modern societies demand high and varied mobility, which in turn requires a complex transport system adapted to social needs that guarantees the movement of people and goods in an economically efficient and safe way, but all are subject to a new environmental rationality and the new logic of the paradigm of sustainability. From this perspective, an efficient and flexible transport system that provides intelligent and sustainable mobility patterns is essential to our economy and our quality of life. The current transport system poses growing and significant challenges for the environment, human health, and sustainability, while current mobility schemes have focused much more on the private vehicle that has conditioned both the lifestyles of citizens and cities, as well as urban and territorial sustainability. Transport has a very considerable weight in the framework of sustainable development due to environmental pressures, associated social and economic effects, and interrelations with other sectors. The continuous growth that this sector has experienced over the last few years and its foreseeable increase, even considering the change in trends due to the current situation of generalized crisis, make the challenge of sustainable transport a strategic priority at local, national, European, and global levels. This Special Issue will pay attention to all those research approaches focused on the relationship between evolution in the area of transport with a high incidence in the environment from the perspective of efficiency

Regular geometry towards effective visitors wayfinding: a case study of KLCC vicinity

In developed cities, large office buildings occupy the city centre thereby destroying the legibility of these areas. These areas confront with a lack of visibility and difficult cognitive map. As a regular spatial configuration, Squares have had an effect on the characteristics of urban space such as intelligibility, synergy and accessibility. The goal of this study is to identify the importance of geometry of space on legibility, cognitive map of visitors and wayfinding. Kuala Lumpur City Centre (KLCC) was chosen as a case study because of its historical and cultural significance. Importance should be placed on its preservation for the future especially for tourists. A model of KLCC has been developed within the square that combines streets and KLCC area. It has been used as proof of the concept for a Space Syntax model network analysis using axial analysis and observations. Meanwhile, this study investigates the views of visitors including 86 respondents using surveys and interviews. Results show that there is a negative correlation between cognitive map and urban stress. Furthermore, all quantitative and qualitative data suggest viable cognitive map due to applying regular geometry may strongly improve legibility. The results show that there was a moderate positive correlation between legibility and regular geometry in general. On the other hand, existing geometry had a negligible effect on legibility. The role of the square suggestion is more immediate in high integration in the vicinity of KLCC. Moreover, the square can provide context for PETRONAS Twin Tower as landmark and symbolic building. Square as regular geometry is a good way to increase viable cognitive map. It affects the legibility of urban space where wayfinding will more strongly confirm that visitors display sociability and accessibility interaction. An implication for architects, tourism managers and urban designers is that square as a regular geometry associated with landmarks increases legibility. As a result, viable cognitive map by regular geometry is associated with easy wayfinding which decreases stress