Impact of Integrated Application of Information Technology on MRMIS

Under the influence of “Digital Earth”, information technology becomes mature, making the procedure of information processing more systematic and integrated. The application and integration of technology like GIS technology, communications and computer network technology, Database Technology, artificial intelligence and expert system technology will play important impact on content of resource information management. In order to discovery the content of impact, we analyze the present situation of mineral resource management information system (MRMIS), summarize the problem. By comparing and analysis, we know the impact of integrated application of IT involves service target, information processing methods, system structure, system function and service content of system. By this, we forecast developing prospect, expected to provide some referred value for development of mineral resource information management

A PSO Approach to Search for Adaptive Trading Rules in the EUA Futures Market

AbstractThe carbon emission futures markets become more and more important in worldwide. More and more counties begin to emphasize environmental protection in the economicdevelopment. Carbon emission trading has become an important part of the energy finance. How to make more profits in the carbon emission futures market is concern by more and more traders and scholars. This paper proposed an approach to search for optimal trading rules in the CO2 allowance futures markets. A group of different moving average trading rules with different weights are used to constitute an integrated trading rule. This is better than a single fixed moving average trading rule.Similarity of trading rules, a parameter we designed, is used to help select basic rules. The authors use static particle swarm optimization process to find the best weights distributions of the selected basic trading rules. After the initial weight distribution is determined, the weights of the basic trading rules will adjusted dynamically every day in the trading process using particle swarm optimization algorithms. Experiments using the EUA Futures Market price data were conducted to find out best adaptive trading rules in the carbon emission futures market. According to our results, it is not necessary to use two moving average trading rules that making same investment advice at a probability higher than 70%. The results show this approach have good performance in adjusting the weights according to the price changes. We found that the adaptive trading rules can help traders make profit in the EUA Futures Marketexcept extreme specialcircumstancesafter price change significantly. This approach might be helpful for traders to make scientificdecision in actual investments

Environmental and economic sustainability of key sectors in China's steel industry chain: An application of the Emergy Accounting approach

Abstract Increasing urbanization day–by–day requires new housing and transportation infrastructures. As a consequence, demand for steel – a basic material for buildings construction as well as for vehicles and railroads – would also increases. This study applies Emergy Accounting (EMA) to assess the Chinas steel industry environmental performance and to identify key application sectors. Subsequently, this study calculates emergy–based indicators capable to assess the present economic performance, environmental sustainability, and land resource appropriate utilization. Building on these indicators, changes of sustainability scenarios in key application sectors are also investigated, with special focus on increased use of recycled steel. The results show that the environmental impacts of steel use in downstream sectors, specially in the Housing and Vehicles Sectors, are significantly higher. Furthermore, the downstream sectors also have a very large requirement for embodied land. Additionally, the Emergy Benefit Ratio (EBR) shows non-negligible advantages to China derived from importing raw iron from abroad at international market prices. Finally, when the recycling rate of scrap steel increases, the performance of downstream sectors improves, with the Vehicle sector showing the most significant changes. Although the benefits of steel-based economy to society are clear, multidimensional sustainability concerns and international competition for primary resources necessitate a transition towards increased recycling and innovative materials within a strictly enforced "circular economy" policy

Generating Moving Average Trading Rules on the Oil Futures Market with Genetic Algorithms

The crude oil futures market plays a critical role in energy finance. To gain greater investment return, scholars and traders use technical indicators when selecting trading strategies in oil futures market. In this paper, the authors used moving average prices of oil futures with genetic algorithms to generate profitable trading rules. We defined individuals with different combinations of period lengths and calculation methods as moving average trading rules and used genetic algorithms to search for the suitable lengths of moving average periods and the appropriate calculation methods. The authors used daily crude oil prices of NYMEX futures from 1983 to 2013 to evaluate and select moving average rules. We compared the generated trading rules with the buy-and-hold (BH) strategy to determine whether generated moving average trading rules can obtain excess returns in the crude oil futures market. Through 420 experiments, we determine that the generated trading rules help traders make profits when there are obvious price fluctuations. Generated trading rules can realize excess returns when price falls and experiences significant fluctuations, while BH strategy is better when price increases or is smooth with few fluctuations. The results can help traders choose better strategies in different circumstances

Centroaffine Bernstein Problems

C.P. Wang [21] studied the Euler-Lagrange equations for the centroaffine area functional of hypersurfaces. We consider classes of examples satisfying these equations together with completeness conditions. We formulate appropriate centroaffine Bernstein problems and give partial solutions

The Multiscale Conformation Evolution of the Financial Time Series

Fluctuations of the nonlinear time series are driven by the traverses of multiscale conformations from one state to another. Aiming to characterize the evolution of multiscale conformations with changes in time and frequency domains, we present an algorithm that combines the wavelet transform and the complex network. Based on defining the multiscale conformation using a set of fluctuation states from different frequency components at each time point rather than the single observable value, we construct the conformational evolution complex network. To illustrate, using data of Shanghai’s composition index with daily frequency from 1991 to 2014 as an example, we find that a few major conformations are the main contributors of evolution progress, the whole conformational evolution network has a clustering effect, and there is a turning point when the size of the chain of multiscale conformations is 14. This work presents a refined perspective into underlying fluctuation features of financial markets

Multiscale Fluctuation Features of the Dynamic Correlation between Bivariate Time Series

The fluctuation of the dynamic correlation between bivariate time series has some special features on the time-frequency domain. In order to study these fluctuation features, this paper built the dynamic correlation network models using two kinds of time series as sample data. After studying the dynamic correlation networks at different time-scales, we found that the correlation between time series is a dynamic process. The correlation is strong and stable in the long term, but it is weak and unstable in the short and medium term. There are key correlation modes which can effectively indicate the trend of the correlation. The transmission characteristics of correlation modes show that it is easier to judge the trend of the fluctuation of the correlation between time series from the short term to long term. The evolution of media capability of the correlation modes shows that the transmission media in the long term have higher value to predict the trend of correlation. This work does not only propose a new perspective to analyze the correlation between time series but also provide important information for investors and decision makers

The Importance of Transfer Function in Solving Set-Union Knapsack Problem Based on Discrete Moth Search Algorithm

Moth search (MS) algorithm, originally proposed to solve continuous optimization problems, is a novel bio-inspired metaheuristic algorithm. At present, there seems to be little concern about using MS to solve discrete optimization problems. One of the most common and efficient ways to discretize MS is to use a transfer function, which is in charge of mapping a continuous search space to a discrete search space. In this paper, twelve transfer functions divided into three families, S-shaped (named S1, S2, S3, and S4), V-shaped (named V1, V2, V3, and V4), and other shapes (named O1, O2, O3, and O4), are combined with MS, and then twelve discrete versions MS algorithms are proposed for solving set-union knapsack problem (SUKP). Three groups of fifteen SUKP instances are employed to evaluate the importance of these transfer functions. The results show that O4 is the best transfer function when combined with MS to solve SUKP. Meanwhile, the importance of the transfer function in terms of improving the quality of solutions and convergence rate is demonstrated as well