International Journal of Applied Mathematics and Computer Sciences最新文献_第10页

Normalized finite fractional differences: Computational and accuracy breakthroughs 归一化有限分数差:计算和精度的突破

International Journal of Applied Mathematics and Computer Sciences Pub Date : 2012-12-01 DOI: 10.2478/v10006-012-0067-9

R. Stanisławski, K. Latawiec

引用次数: 44

Intelligent financial time series forecasting: A complex neuro-fuzzy approach with multi-swarm intelligence 金融时间序列智能预测:一种多群智能的复杂神经模糊方法

International Journal of Applied Mathematics and Computer Sciences Pub Date : 2012-12-01 DOI: 10.2478/v10006-012-0058-x

Chunshien Li, Tai-Wei Chiang

{"title":"Intelligent financial time series forecasting: A complex neuro-fuzzy approach with multi-swarm intelligence","authors":"Chunshien Li, Tai-Wei Chiang","doi":"10.2478/v10006-012-0058-x","DOIUrl":"https://doi.org/10.2478/v10006-012-0058-x","url":null,"abstract":"Financial investors often face an urgent need to predict the future. Accurate forecasting may allow investors to be aware of changes in financial markets in the future, so that they can reduce the risk of investment. In this paper, we present an intelligent computing paradigm, called the Complex Neuro-Fuzzy System (CNFS), applied to the problem of financial time series forecasting. The CNFS is an adaptive system, which is designed using Complex Fuzzy Sets (CFSs) whose membership functions are complex-valued and characterized within the unit disc of the complex plane. The application of CFSs to the CNFS can augment the adaptive capability of nonlinear functional mapping, which is valuable for nonlinear forecasting. Moreover, to optimize the CNFS for accurate forecasting, we devised a new hybrid learning method, called the HMSPSO-RLSE, which integrates in a hybrid way the so-called Hierarchical Multi-Swarm PSO (HMSPSO) and the wellknown Recursive Least Squares Estimator (RLSE). Three examples of financial time series are used to test the proposed approach, whose experimental results outperform those of other methods.","PeriodicalId":253470,"journal":{"name":"International Journal of Applied Mathematics and Computer Sciences","volume":"57 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126532207","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 157

Designing a ship course controller by applying the adaptive backstepping method 应用自适应反步法设计船舶航向控制器

International Journal of Applied Mathematics and Computer Sciences Pub Date : 2012-12-01 DOI: 10.2478/v10006-012-0073-y

A. Witkowska, R. Smierzchalski

引用次数: 38

A rainfall forecasting method using machine learning models and its application to the Fukuoka city case 基于机器学习模型的降雨预报方法及其在福冈市案例中的应用

International Journal of Applied Mathematics and Computer Sciences Pub Date : 2012-12-01 DOI: 10.2478/v10006-012-0062-1

S. Sumi, F. Zaman, H. Hirose

{"title":"A rainfall forecasting method using machine learning models and its application to the Fukuoka city case","authors":"S. Sumi, F. Zaman, H. Hirose","doi":"10.2478/v10006-012-0062-1","DOIUrl":"https://doi.org/10.2478/v10006-012-0062-1","url":null,"abstract":"In the present article, an attempt is made to derive optimal data-driven machine learning methods for forecasting an average daily and monthly rainfall of the Fukuoka city in Japan. This comparative study is conducted concentrating on three aspects: modelling inputs, modelling methods and pre-processing techniques. A comparison between linear correlation analysis and average mutual information is made to find an optimal input technique. For the modelling of the rainfall, a novel hybrid multi-model method is proposed and compared with its constituent models. The models include the artificial neural network, multivariate adaptive regression splines, the k-nearest neighbour, and radial basis support vector regression. Each of these methods is applied to model the daily and monthly rainfall, coupled with a pre-processing technique including moving average and principal component analysis. In the first stage of the hybrid method, sub-models from each of the above methods are constructed with different parameter settings. In the second stage, the sub-models are ranked with a variable selection technique and the higher ranked models are selected based on the leave-one-out cross-validation error. The forecasting of the hybrid model is performed by the weighted combination of the finally selected models.","PeriodicalId":253470,"journal":{"name":"International Journal of Applied Mathematics and Computer Sciences","volume":"35 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132518961","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 76

Regulation of p53 by siRNA in radiation treated cells: Simulation studies 辐射处理细胞中siRNA对p53的调控:模拟研究

International Journal of Applied Mathematics and Computer Sciences Pub Date : 2012-12-01 DOI: 10.2478/v10006-012-0075-9

K. Puszyński, R. Jaksik, A. Świerniak

{"title":"Regulation of p53 by siRNA in radiation treated cells: Simulation studies","authors":"K. Puszyński, R. Jaksik, A. Świerniak","doi":"10.2478/v10006-012-0075-9","DOIUrl":"https://doi.org/10.2478/v10006-012-0075-9","url":null,"abstract":"Ionizing radiation activates a large variety of intracellular mechanisms responsible for maintaining appropriate cell functionality or activation of apoptosis which eliminates damaged cells from the population. The mechanism of such induced cellular death is widely used in radiotherapy in order to eliminate cancer cells, although in some cases it is highly limited by increased cellular radio-resistance due to aberrations in molecular regulation mechanisms of malignant cells. Despite the positive correlation between the radiation dose and the number of apoptotic cancer cells, radiation has to be limited because of extensive side effects. Therefore, additional control signals whose role will be to maximize the cancer cells death-ratio while minimizing the radiation dose and by that the potential side effects are worth considering. In this work we present the results of simulation studies showing possibilities of single gene regulation by small interfering RNA (siRNA) that can increase radio-sensitivity of malignant cells showing aberrations in the p53 signaling pathway, responsible for DNA damage-dependant apoptosis. By blocking the production of the p53 inhibitor Mdm2, radiation treated cancer cells are pushed into the apoptotic state on a level normally achievable only with high radiation doses. The presented approach, based on a simulation study originating from experimentally validated regulatory events, concerns one of the basic problems of radiotherapy dosage limitations, which, as will be shown, can be partially avoided by using the appropriate siRNA based control mechanism.","PeriodicalId":253470,"journal":{"name":"International Journal of Applied Mathematics and Computer Sciences","volume":"24 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-12-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127703818","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 16

Infinite-dimensional Sylvester equations: Basic theory and application to observer design 无限维Sylvester方程:基本理论及其在观测器设计中的应用

International Journal of Applied Mathematics and Computer Sciences Pub Date : 2012-06-01 DOI: 10.2478/v10006-012-0018-5

Z. Emirsajlow

引用次数: 9

Neuro-rough-fuzzy approach for regression modelling from missing data 缺失数据回归建模的神经粗糙模糊方法

International Journal of Applied Mathematics and Computer Sciences Pub Date : 2012-06-01 DOI: 10.2478/v10006-012-0035-4

Krzysztof Siminski

引用次数: 20

Existence and determination of the set of Metzler matrices for given stable polynomials 给定稳定多项式的Metzler矩阵集的存在性与确定

International Journal of Applied Mathematics and Computer Sciences Pub Date : 2012-06-01 DOI: 10.2478/v10006-012-0029-2

T. Kaczorek

引用次数: 21

Improving prediction models applied in systems monitoring natural hazards and machinery 改进用于自然灾害和机械监测系统的预测模型

International Journal of Applied Mathematics and Computer Sciences Pub Date : 2012-06-01 DOI: 10.2478/v10006-012-0036-3

M. Sikora, B. Sikora

{"title":"Improving prediction models applied in systems monitoring natural hazards and machinery","authors":"M. Sikora, B. Sikora","doi":"10.2478/v10006-012-0036-3","DOIUrl":"https://doi.org/10.2478/v10006-012-0036-3","url":null,"abstract":"Improving prediction models applied in systems monitoring natural hazards and machinery A method of combining three analytic techniques including regression rule induction, the k-nearest neighbors method and time series forecasting by means of the ARIMA methodology is presented. A decrease in the forecasting error while solving problems that concern natural hazards and machinery monitoring in coal mines was the main objective of the combined application of these techniques. The M5 algorithm was applied as a basic method of developing prediction models. In spite of an intensive development of regression rule induction algorithms and fuzzy-neural systems, the M5 algorithm is still characterized by the generalization ability and unbeatable time of data model creation competitive with other systems. In the paper, two solutions designed to decrease the mean square error of the obtained rules are presented. One consists in introducing into a set of conditional variables the so-called meta-variable (an analogy to constructive induction) whose values are determined by an autoregressive or the ARIMA model. The other shows that limitation of a data set on which the M5 algorithm operates by the k-nearest neighbor method can also lead to error decreasing. Moreover, three application examples of the presented solutions for data collected by systems of natural hazards and machinery monitoring in coal mines are described. In Appendix, results of several benchmark data sets analyses are given as a supplement of the presented results.","PeriodicalId":253470,"journal":{"name":"International Journal of Applied Mathematics and Computer Sciences","volume":"32 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2012-06-01","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132049875","PeriodicalName":null,"FirstCategoryId":null,"ListUrlMain":null,"RegionNum":0,"RegionCategory":"","ArticlePicture":[],"TitleCN":null,"AbstractTextCN":null,"PMCID":"","EPubDate":null,"PubModel":null,"JCR":null,"JCRName":null,"Score":null,"Total":0}

引用次数: 18

LMI optimization problem of delay-dependent robust stability criteria for stochastic systems with polytopic and linear fractional uncertainties 具有多面体和线性分数阶不确定性随机系统时滞相关鲁棒稳定性准则的LMI优化问题

International Journal of Applied Mathematics and Computer Sciences Pub Date : 2012-06-01 DOI: 10.2478/v10006-012-0025-6

P. Balasubramaniam, S. Lakshmanan, R. Rakkiyappan

引用次数: 10