BASIC EQUATIONS, THEORY AND PRINCIPLE OF COMPUTATIONAL STOCK MARKET (Ⅰ)──BASIC EQUATIONS

This paper studies computational stock market by using network model and similar methodology used in solid mechanics. Four simultaneous basic equations, i. e., equation of interest rate and amount of circulating fond, equations of purchasing and selling of share, equation of changing rate of share price, and equation of interest rate, share price and its changing rate, have been established. Discussions mainly on the solution and its simple applications of the equation of interest rate and amount of circulating fond are given. The discussions also involve the proof of tending to the equilibrium state of network of stock market based on the time discrete form of the equation by using Banach theorem of contraction mapping, and the influence of amount of circulating fond with exponential attenuation due to the decreasing of banking interest rate.Keyworks: stock market; network model; differential equation; contraction mapping; elasticity; methodology

Computational Intelligence Determines Effective Rationality

Rationality is a fundamental concept in economics. Most researchers will accept that human beings are not fully rational. Herbert Simon suggested that we are ＂bounded rational＂. However, it is very difficult to quantify ＂bounded rationality＂, and therefore it is difficult to pinpoint its impact to all those economic theories that depend on the assumption of full rationality. Ariel Rubinstein proposed to model bounded rationality by explicitly specifying the decision makers＇ decision-making procedures. This paper takes a computational point of view to Rubinstein＇s approach. From a computational point of view, decision procedures can be encoded in algorithms and heuristics. We argue that, everything else being equal, the effective rationality of an agent is determined by its computational power - we refer to this as the computational intelligence determines effective rationality （CIDER） theory. This is not an attempt to propose a unifying definition of bounded rationality. It is merely a proposal of a computational point of view of bounded rationality. This way of interpreting bounded rationality enables us to （computationally） reason about economic systems when the full rationality assumption is relaxed.

Creation mechanism of electron-positron pair on equally spaced multiple localized fields

We investigate the electron-positron creation process from multiple equally spaced distributed oscillating electric fields.The computational quantum field theory(CQFT)is applied to analyze the effect of the number of local fields,the distance between them,and their potential height on the created particle number.It is found that whether adjacent electric fields overlap plays an important role.The creation rate exhibits a direct linear relationship with the number of fields when they do not overlap,but exceeds the sum of the rate when the fields alone.They exhibit a distinctly nonlinear relationship when they overlap,and in particular exhibit a quadratic relationship when the fields completely overlap.These phenomena corroborate that the particle pair creation in the interaction region is non-uniform and influenced by the strength of the central strongest electric field.

Enhancement of electron–positron pairs in combined potential wells with linear chirp frequency

Effect of linear chirp frequency on the process of electron–positron pairs production from vacuum is investigated by the computational quantum field theory.With appropriate chirp parameters,the number of electrons created under combined potential wells can be increased by two or three times.In the low frequency region,frequency modulation excites interference effect and multiphoton processes,which promotes the generation of electron–positron pairs.In the high frequency region,high frequency suppression inhibits the generation of electron–positron pairs.In addition,for a single potential well,the number of created electron–positron pairs can be enhanced by several orders of magnitude in the low frequency region.

Time Complexity of Evolutionary Algorithms for Combinatorial Optimization:A Decade of Results

Computational time complexity analyzes of evolutionary algorithms （EAs） have been performed since the mid-nineties. The first results were related to very simple algorithms, such as the （1＋1）-EA, on toy problems. These efforts produced a deeper understanding of how EAs perform on different kinds of fitness landscapes and general mathematical tools that may be extended to the analysis of more complicated EAs on more realistic problems. In fact, in recent years, it has been possible to analyze the （1＋1）-EA on combinatorial optimization problems with practical applications and more realistic population-based EAs on structured toy problems. This paper presents a survey of the results obtained in the last decade along these two research lines. The most common mathematical techniques are introduced, the basic ideas behind them are discussed and their elective applications are highlighted. Solved problems that were still open are enumerated as are those still awaiting for a solution. New questions and problems arisen in the meantime are also considered.

Impact of the equivalent center of mass separating from the sliding surface on the isolation performance of friction pendulum bearings

A new equivalent center of mass model of FPBs (friction pendulum bearings) is introduced, and based on this model, coefficient j of the equivalent center of mass separating from the sliding surface is defined. It is thought in theory that j has a significant impact on the isolation parameter of FPBs, since the equivalent post-yielding stiffness and friction coefficients are not simply determined by sliding radius and sliding friction pairs. The results of numerical simulation analysis using ABAQUS conducted on two groups of FPBs support this viewpoint. For FPBs with the same sliding radius and sliding friction pairs, the FPB modules of structural analysis software such as ETABS could only distinguish the equivalent transformation using j one by one. The seismic response data obtained in a base isolation calculation example of FPBs are very different, which reveals that j’s impact on the isolation effectiveness of FPBs cannot be ignored. The introduction of j will help improve the classical structural theory of FPBs and the weak points of structural analysis software based on this theory, which is important in achieving more accurate analyses in structural design.

AXIAL HEAT CONDUCTION MODEL TO PREDICT MAXIMUM HEAT REMOVE OF MINIATURE HEAT PIPE BASED ON GREY MODEL THEORY

Computer chip is always accompanied by the increase of heat dissipation and miniaturization. The miniature heat pipes are widely used in notebook computer to resolve the heat dissipation problems. Maximum heat removed model of miniature heat pipes building by grey model is presented. In order to know the foundation for modeling, the smooth grade of error examination is inquired and the accuracy of grey relational grade is verified. The model can be used to select a suitable heat pipes to solve electric heat problems in the future. Final results show that the grey model only needs four experiment data and its error value is less than 10%, further, it is better than computational fluid dynamics （CFD） model.

Creation and annihilation phenomena of electron and positron pairs in an oscillating field

The combination of an oscillating and a static field is used to study the creation and annihilation phenomena during the pair creation process.The time evolution,spatial density and momentum distribution of the created particles for a fermionic system are presented,which demonstrate that with the increasing static field intensity,the number of the created particles experiences a distinguishable decrease in every period of the oscillating field,which is caused by the annihilation phenomena between the created electrons and positrons.

Progress in Computational Complexity Theory

We briefly survey a number of important recent uchievements in Theoretical Computer Science （TCS）, especially Computational Complexity Theory. We will discuss the PCP Theorem, its implications to inapproximability on combinatorial optimization problems; space bounded computations, especially deterministic logspace algorithm for undirected graph connectivity problem; deterministic polynomial-time primality test; lattice complexity, worst-case to average-case reductions; pseudorandomness and extractor constructions; and Valiant＇s new theory of holographic algorithms and reductions.

THE EMERGING CHALLENGE:THE VALIDITY OF COMPUTATIONAL ORGANIZATION MODEL AND METHODOLOGY

The validity of the computational organization model is a necessary condition and also poses a bottleneck in computational organization theory development.Established on the frontline of computational organization theory,this paper provides an overall discussion on the difficulties in validation and validation methodology of the computational organization model.First,different from natural engineering system model,and also exceeding the traditional empirical method,the computational organization model is faced with various subjective and objective difficulties during the validation progress;second,in developing the situational validation methodology based on relationships among problem field,modeling purpose and referents,it is important for the computational organization model that the validation is conducted according to certain degree;third,the establishment of verification,validation and accreditation approach(VV&A),which is different from the natural engineering system,is an irresistible trend for future development of the computational organization model.Model validation should be focused on concept validation,operation validation,and data validation,as well as the principle of iterative validation approach and such validation should be conducted throughout the modeling process;finally,the validation of computational organization model should be the process to enhance people’s confidence in the model.From the perspective of review,if the model is able to pass through all the validation tests,it is helpful for a better understanding of the model’s ability,limitation and applicability.In this case,research from interdisciplinary experts is required urgently.

Single-atom rhodium anchored on S-doped black phosphorene as a promising bifunctional electrocatalyst for overall water splitting

Superior bifunctional electrocatalysts with ultra-high stability and excellent efficiency are crucial to boost the oxygen evolution reaction(OER) and the hydrogen evolution reduction(HER) in the overall water splitting(OWS) for the sustainable production of clean fuels. Herein, comprehensive density functional theory(DFT) computations were performed to explore the potential of several single transition metal(TM) atoms anchored on various S-doped black phosphorenes(TM/Snx-BP) for bifunctional OWS electrocatalysis. The results revealed that these candidates display good stability, excellent electrical conductivity, and diverse spin moments. Furthermore, the Rh/S12-BP catalyst was identified as an eligible bifunctional catalyst for OWS process due to the low overpotentials for OER(0.43 V) and HER(0.02 V), in which Rh and its adjacent P atoms were identified as the active sites. Based on the computed Gibbs free energies of OH~*, O~*, OOH~* and H~*, the corresponding volcano plots for OER and HER were established.Interestingly, the spin moments and the charge distribution of the active sites determine the catalytic trends of OER and HER. Our findings not only propose a promising bifunctional catalyst for OWS, but also widen the potential application of BP in electrocatalysis.

Layered virtual machine migration algorithm for network resource balancing in cloud computing

Due to the increasing sizes of cloud data centers, the number of virtual machines （VMs） and applications rises quickly. The rapid growth of large scale Internet services re- suits in unbalanced load of network resource. The bandwidth utilization rate of some physical hosts is too high, and this causes network congestion. This paper presents a layered VM migration algorithm （LVMM）. At first, the algorithm will divide the cloud data center into several regions according to the bandwidth utilization rate of the hosts. Then we bal- ance the load of network resource of each region by VM migrations, and ultimately achieve the load balance of net- work resource in the cloud data center. Through simulation experiments in different environments, it is proved that the LVMM algorithm can effectively balance the load of network resource in cloud computing.

An Energy-Saving Task Scheduling Strategy Based on Vacation Queuing Theory in Cloud Computing

High energy consumption is one of the key issues of cloud computing systems. Incoming jobs in cloud computing environments have the nature of randomness, and compute nodes have to be powered on all the time to await incoming tasks. This results in a great waste of energy. An energy-saving task scheduling algorithm based on the vacation queuing model for cloud computing systems is proposed in this paper. First, we use the vacation queuing model with exhaustive service to model the task schedule of a heterogeneous cloud computing system.Next, based on the busy period and busy cycle under steady state, we analyze the expectations of task sojourn time and energy consumption of compute nodes in the heterogeneous cloud computing system. Subsequently, we propose a task scheduling algorithm based on similar tasks to reduce the energy consumption. Simulation results show that the proposed algorithm can reduce the energy consumption of the cloud computing system effectively while meeting the task performance.

Analyses and computations of asymmetric Z-scan for large phase shift from diffraction theory

Based on Presnel-Kirchhoff diffraction theory, we set up a diffraction model of nonlinear optical media to Gaussian beam, which can interpret the Z-scan phenomenon from a new way. This theory is not only well consistent with the conventional Z-scan theory in the case of small nonlinear phase shift, but also can fit for the lager nonlinear phase shift. Numeric computations indicate the shape of the Z-scan curve is greatly affected by the value of the nonlinear phase shift. The symmetric dispersion-like Z-scan curve is only valid for small nonlinear phase shift (|Δφ0| < π), but with increasing the nonlinear phase shift, the valley of the transmittance is severely suppressed and the peak is greatly enhanced. Further calculations show some new interesting results.

A version of Geiringer-like theorem for decision making in the environments with randomness and incomplete information

Purpose-The purpose of this paper is to establish a version of a theorem that originated from population genetics and has been later adopted in evolutionary computation theory that will lead to novel Monte-Carlo sampling algorithms that provably increase the AI potential.Design/methodology/approach-In the current paper the authors set up a mathematical framework,state and prove a version of a Geiringer-like theorem that is very well-suited for the development of Mote-Carlo sampling algorithms to cope with randomness and incomplete information to make decisions.Findings-This work establishes an important theoretical link between classical population genetics,evolutionary computation theory and model free reinforcement learning methodology.Not only may the theory explain the success of the currently existing Monte-Carlo tree sampling methodology,but it also leads to the development of novel Monte-Carlo sampling techniques guided by rigorous mathematical foundation.Practical implications-The theoretical foundations established in the current work provide guidance for the design of powerful Monte-Carlo sampling algorithms in model free reinforcement learning,to tackle numerous problems in computational intelligence.Originality/value-Establishing a Geiringer-like theorem with non-homologous recombination was a long-standing open problem in evolutionary computation theory.Apart from overcoming this challenge,in a mathematically elegant fashion and establishing a rather general and powerful version of the theorem,this work leads directly to the development of novel provably powerful algorithms for decision making in the environment involving randomness,hidden or incomplete information.