Using jump-diffusion modeling for valuing real options in infrastructure projects

In infrastructure financed projects, in order to attract private investors, host governments often provide some guarantees. This paper develops a value model of minimum revenue guarantee with multiple-exercise real options under the impact of the emergency incident. The model is applied to infrastructure financed projects using the minimum revenue guarantee under simulation. The simulation results indicate that, before quantifying the value of the minimum revenue guarantee, it is necessary to forecast the jump degree and intensity of the emergency incident, as well as prevent and control risks arising from such emergencies. Otherwise, underestimation of the guarantee value will occur and the government will have to bear huge debt in this condition. We also analyze the dependence of the guaranteed value on the minimum guaranteed revenue level, initial revenue and number of exercise rights. For various conditions, the diagrams of the guaranteed value are also presented.     

Handling multi-objective optimization problems with a multi-swarm cooperative particle swarm optimizer

This paper presents a new multi-objective optimization algorithm in which multi-swarm cooperative strategy is incorporated into particle swarm optimization algorithm, called multi-swarm cooperative multi-objective particle swarm optimizer (MC-MOPSO). This algorithm consists of multiple slave swarms and one master swarm. Each slave swarm is designed to optimize one objective function of the multi-objective problem in order to find out all the non-dominated optima of this objective function. In order to produce a well distributed Pareto front, the master swarm is developed to cover gaps among non-dominated optima by using a local MOPSO algorithm. Moreover, in order to strengthen the capability locating multiple optima of the PSO, several improved techniques such as the Pareto dominance-based species technique and the escape strategy of mature species are introduced. The simulation results indicate that our algorithm is highly competitive to solving the multi-objective optimization problems.     

基于二次TF* IDF的互信息文本特征选择算法研究

在分析传统互信息法缺陷的基础上,提出一种基于二次TF*IDF的互信息特征选择算法,对仅在一个类别中出现的特征词的重要程度给予再次的衡量,解决了互信息值相等而无法进行有效特征选择的问题。利用贝叶斯分类器对该方法进行验证的结果表明该算法在文本分类效率和正确率上比原有方法有一定的提高。     

High sensitive and selective formaldehyde sensors based on nanoparticle-assembled ZnO micro-octahedrons synthesized by homogeneous precipitation method

Nanoparticle-assembled ZnO micro-octahedrons were synthesized by a facile homogeneous precipitation method. The ZnO micro-octahedrons are hexagonal wurtzite with high crystallinity. Abundant structure defects were confirmed on ZnO surface by photoluminescence. Gas sensors based on the ZnO micro-octahedrons exhibited high response, selectivity and stability to 1–1000 ppm formaldehyde at 400 °C. Especially, even 1 ppm formaldehyde could be detected with high response (S = 22.7). It is of interest to point out that formaldehyde could be easily distinguished from ethanol or acetaldehyde with a selectivity of about 3. The high formaldehyde response is mainly attributed to the synergistic effect of high contents of electron donor defects (Zn_i and V_O) and highly active oxygen species (O²⁻) on the ZnO surface.     

Necessary conditions of optimality for a class of optimal control problems on time scales

A class of optimal control problems of a system governed by linear dynamic equations on time scales with quadratic cost functional is considered. By the Lebesgue Δ-integral theory and the Sobolev-type space H¹ on time scales the weak solution of linear dynamic equations on time scales for both initial value problem and backward problem are introduced, therefore the necessary conditions of optimality are presented. Some typical examples are given for demonstration.     

一种基于熵的文本相似性计算方法

文本比较是求解两个文本间相似度的过程,文本间的相似度越高代表两个文本越趋于类似。传统的相似度算法主要从字符的角度度量文本的相似性,而忽略了文本内多个共同文本串对于文本相似度的影响。针对此问题,本文提出一种基于熵的相似度求解方法。该方法在对文本间字符信息的提取基础上,建立共同子文本串度量维度,然后采用熵的方法进行相似度度量。实验表明,该方法具有更平滑的相似度曲线,验证了算法的有效性和准确性。     

Similarity-based image organization and browsing using multi-resolution self-organizing map

An algorithm is presented in this paper to facilitate the exploration of large image collections based on visual similarities. Starting with an unordered and unannotated set of images, the algorithm first extracts the salient details into feature vectors using both color and gradient information. The feature vectors are then used to train a self-organizing map which maps high-dimensional feature vectors onto a 2D canvas so that images with similar feature vectors are grouped together. When users browse the image collection, an image collage is generated that selects and displays the most pertinent set of images based on which portion of the 2D canvas is currently in view. Flowing from an overview to details is a seamless operation controlled simply by pan and zoom, with representative images selected in a consistent and predictable way. To make organizing larger image collections practical in interactive time, the organization algorithm is designed to run in parallel on graphics processing units. Overall this paper presents an end-to-end solution that facilitates the surfing of image collections in a fresh way.     

基于智能流量预测的入侵检测方法

为了提高入侵检测系统检测的实时性,提出了一种基于智能流量预测的入侵检测方法。该方法拟合了智能Agent的智能性、自主性和自适应性的优点以及灰色预测对不确定资源的科学预测的优点,用流量预测智能Agent预测得到的流量序列来代替未来一段时间段内的实际流量,并把这个预测序列作为检测对象集的一部分。然后用人工方法模拟了流量处理Agent与预测智能Agent的活动,并通过对实际的采集数据进行仿真,实验证明了预测智能Agent的预测活动的科学性。