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In this paper, a numerical prediction method called addition-subtraction frequency (ASF) method with 3 inputs and full traversal is presented, in order to predict USA future wars. In the last few years, several wars around the world that were all related to the United States of America burst out, such as War in Afghanistan, Iraq War, War in North-West Pakistan and Libyan Civil War, which caused a...
A numerical prediction algorithm called addition-subtraction frequency (ASF) algorithm is presented in this paper to predict potential valley-point dates of stock market. In the paper, we use historical valley-point date data of Shanghai Security Exchange (SSE) Composite Index as the input of ASF algorithm. According to the Royal Swedish Academy of Sciences, the stock prediction in the next three...
As one of the most influential and changeable factors, temperature has always been an important research object. Since temperature is affected by many factors, all of them contribute in the formation of the temperature curve. We can obtain the regular pattern of influence factors by decomposing temperature data. In this paper, a new method is proposed, which is named average-type multiple sine-related...
Japan has the highest debt-to-GDP ratio among advanced countries. Japanese central government debt has increased rapidly in the past 20 years. According to the data provided by Ministry of Finance, Japan, the total central government debt (TCGD) of Japan reached ¥1, 066,423.4 billion (December 31, 2016). This number refreshes the history record of Japanese central government debt. It is important...
A prediction attempt for next potential Mw8.1-or-above earthquake in Japan before 2020 is presented in this work via addition-subtraction frequency (ASF) method. ASF method can be configured as a model of 3, 5 or 7 variables. This paper uses the historical date data of earthquake occurrence in Japan from 1854 to 2011, and transforms them into three forms [i.e., m/d/y (month/day/year), m/y (month/year),...
A momentous social event prediction attempt is presented in this work. Addition-subtraction frequency (ASF) algorithm with three inputs is investigated and employed to predict a possible date of the event. The important date data which this paper uses are the dates of United States' president death in office (USPDIO) in the past. In order to find a consistent prediction result, three forms of USPDIO...
In this work, we present a hypothesis about a potential major internal crisis (MIC) season in the future of the United States (US). Specifically, analyzing the surrounding, population and financial problems faced by the United States, with the aid of 3-layer feedforward neuronets (FN) equipped with weights-and-structure-determination (WASD) algorithm, we get the hypothesis with relatively high reliability...
In modern engineering researches, dynamics of systems are often studied by well-design computer simulations, and these dynamics are usually depicted in the form of vector-or matrix-valued ordinary differential equation (ODE) systems. A common approach for solution of matrix-valued ODE in MATLAB is to use the Kronecker product and vectorization technique. However, the vectorization procedure may be...
Cooperative co-evolution framework has been developed for solving large scale global optimization problems. This approach applies the divide-and-conquer strategy that decomposes the problem into subcomponents which can be optimized separately. Nevertheless, the decomposition strategy has important influence on solution quality. In theory, the interdependency between subcomponents should be kept minimum...
Traditional particle swarm optimization algorithms (PSO) targeted to solve large scale problems are mostly serial, such as CCPSO2, and the computing time is very long in general. Therefore, this paper presents a novel parallel PSO, which explores the usage of new probability distribution functions for the replacement of traditional Gaussian and Cauchy distributions, and the combination of GPSO and...
Zhang neural network (ZNN) is a novel class of recurrent neural network with superior solution ability and convergence performance. For real-time solution of Moore-Penrose pseudoinverses of time-varying matrices based on continuous-time recurrent neural network, this paper proposes three different ZNN models, each of which is derived from a specifically-chosen Zhang function (ZF). Theoretical analyses...
This paper demonstrates the flexibility of Z-type methodology for generating multiple solution-models of time-varying problems. As a case study with examples, we investigate the solution of time-varying generalized inverse (termed Zhang generalized inverse, ZGI). Specifically, to solve for time-varying left generalized inverse (TVLGI or termed Zhang left generalized inverse, ZLGI), five different...
Recently, a special class of recurrent neural network (termed Zhang neural network, ZNN) has been generalized for solving systems of time-varying nonlinear equations (STVNE), and a resultant continuous (or say, continuous-time) ZNN model has been proposed and analyzed. To generalize the idea for digital computers and numerical algorithms, this paper discretizes the continuous STVNE-solving ZNN using...
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