Time difference of arrival (TDoA) based on a group of sensor nodes with known locations has been widely used to locate targets. Two-step weighted least squares (TSWLS), constrained weighted least squares (CWLS), and Newton–Raphson (NR) iteration are commonly used passive location methods, among which the initial position is needed and the complexity is high. This paper proposes a hybrid firefly algorithm (hybrid-FA) method, combining the weighted least squares (WLS) algorithm and FA, which can reduce computation as well as achieve high accuracy. The WLS algorithm is performed first, the result of which is used to restrict the search region for the FA method. Simulations showed that the hybrid-FA method required far fewer iterations than the FA method alone to achieve the same accuracy. Additionally, two experiments were conducted to compare the results of hybrid-FA with other methods. The findings indicated that the root-mean-square error (RMSE) and mean distance error of the hybrid-FA method were lower than that of the NR, TSWLS, and genetic algorithm (GA). On the whole, the hybrid-FA outperformed the NR, TSWLS, and GA for TDoA measurement.
Most tests are administered within an allocated time. Due to the time limit, examinees might have different trade-offs on different items. In educational testing, the traditional hierarchical model cannot adequately account for the tradeoffs between response time and accuracy. Because of this, some joint models were developed as an extension of the traditional hierarchical model based on covariance. However, they cannot directly reflect the dynamic relationship between response time and accuracy. In contrast, response moderation models took the residual response time as the independent variable of the response model. Nevertheless, the models enlarge the time effect. Alternatively, the speed-accuracy tradeoff (SAT) model is superior to other experimental models in the SAT experiment. Therefore, this paper incorporates the SAT model with the traditional hierarchical model to establish a SAT hierarchical model. The results demonstrated that the Bayesian Markov chain Monte Carlo (MCMC) algorithm performed well in the SAT hierarchical model of parameters by using simulation. Finally, the deviance information criterion (DIC) more preferred the SAT hierarchical model than other models in empirical data. This means that it is indispensable to add the effect of response time on accuracy, but likewise should limit the effect on the empirical data.
Purpose -Fraudulent financial statements and the manipulation of stock prices can seriously affect investors' judgment of company performance, especially in stock markets in emerging economies. Apart from financial reports, which run the risk of being misreported, are there any other information sources that the public can trust when it comes to the truth about a company's performance? The purpose of this paper is to address this issue by assessing the correlation between online recruitment information and company performance and provide investors with a new framework to assist them in making decisions and to identify fraud. Design/methodology/approach -The research extracted the recruitment information of normal and fraudulent companies separately from the internet by employing techniques of natural language processing, opinion mining and competitive intelligence. A statistical tool was then used to study whether there is a difference in the correlation between the recruitment information intensity (RII) and the annually averaged stock price (AASP) of normal and fraudulent firms. Findings -The experiments showed that recruitment information intensity is significantly correlated to company's stock performance for normal firms, which indicates that the company's recruitment activities are consistent with their performance. But for fraudulent companies, the fact that the result is quite the opposite may imply that the RII discloses the truth when managers make misreports. Practical implications -The findings suggest that the intensity of a company's recruitment information is a valuable element for investors in evaluating the firm, and it also can be used as a reliable tool to assist in identifying fraudulent companies. Originality/value -This paper provided a novel way for the public to break information barriers to reach the truth of companies' performance and avoid misleading fraudulent finance statements. It is also a useful application of natural language processing techniques.
In this paper, we illustrated the shortcomings of combat model (Lanchester Equations), introduced the development of combat simulation recently, proposed the approach of combat simulation and modeling and a kind of abstract structure of weapon platform based on complex systems theory. In the last, we provided a combat example t o illustrate our approach i n details.
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