Yanzhen Wang¹, Xuefeng Yan^1,*

CMES-Computer Modeling in Engineering & Sciences, Vol.121, No.1, pp. 123-144, 2019, DOI:10.32604/cmes.2019.07052

Abstract A single model cannot satisfy the high-precision prediction requirements given the high nonlinearity between variables. By contrast, ensemble models can effectively solve this problem. Three key factors for improving the accuracy of ensemble models are namely the high accuracy of a submodel, the diversity between subsample sets and the optimal ensemble method. This study presents an improved ensemble modeling method to improve the prediction precision and generalization capability of the model. Our proposed method first uses a bagging algorithm to generate multiple subsample sets. Second, an indicator vector is defined to describe these subsample sets. More >

Weijin Jiang^1,2,3, Jiahui Chen^1,*, Yirong Jiang^4,*, Yuhui Xu¹, Yang Wang¹, Lina Tan¹, Guo Liang⁵

CMC-Computers, Materials & Continua, Vol.61, No.2, pp. 849-859, 2019, DOI:10.32604/cmc.2019.05932

Abstract Aiming at the problem that the traditional collaborative filtering recommendation algorithm does not fully consider the influence of correlation between projects on recommendation accuracy, this paper introduces project attribute fuzzy matrix, measures the project relevance through fuzzy clustering method, and classifies all project attributes. Then, the weight of the project relevance is introduced in the user similarity calculation, so that the nearest neighbor search is more accurate. In the prediction scoring section, considering the change of user interest with time, it is proposed to use the time weighting function to improve the influence of the More >

Sujit Sil^{1, 2}, Tanmoy Mallick², Tuhin Pal¹, Animesh Mondal¹, Kalyan Kumar De¹ and Asok Ghosh^2,*

Phyton-International Journal of Experimental Botany, Vol.88, No.3, pp. 295-315, 2019, DOI:10.32604/phyton.2019.06907

Abstract The genus Saraca L. (Leguminosae) is a universal panacea in herbal medicine. The present study investigates the comparative pollen morphology of four species of Saraca viz. S. asoca (Roxb.) de Wilde, S. declinata (Jack) Miq., S. indica L., and S. thaipingensis Cantley ex Prain growing in India to reveal differences of their pollen structures to aid taxonomic and evolutionary values. The detailed morphology and surface structure of pollen grains were studied and described using light microscopy and scanning electron microscopy. The pollen grains of Saraca showed isopolar, para-syncolporate, tricolporate, with radially symmetric, prolate and prolate-spheroidal… More >

Ozturk M¹, S Gucel², V Altay³, MSA Ahmad⁴, MY Ashraf⁵, M Ashraf⁶

Phyton-International Journal of Experimental Botany, Vol.88, No.1, pp. 63-68, 2019, DOI:10.32604/phyton.2019.04574

Abstract This paper presents the work conducted on the chemical constituents of some common and widely distributed halophyte taxa from Cyprus with the aim that these studies will help in the evaluation of halophytes for different economical purposes. The plant species of Crithmum maritimum L., Limbarda crithmoides (L.) Dumort, Atriplex portulacoides L., Salsola kali L., Atriplex halimus L., Limonium oleifolium Mill., L. meyeri (Boiss.) Kuntze; and Tetraena alba (L.f.) Beier & Thulin were collected in the middle of July. The shoot tissue and leaf samples were collected from the natural habitats and left for drying under… More >

Shouzhou Gu^1,*, Jinzhong Bei¹, Chuang Shi², Yaming Dang¹, Zuoya Zheng⁴, Congcong Cui⁵

CMES-Computer Modeling in Engineering & Sciences, Vol.119, No.2, pp. 281-293, 2019, DOI:10.32604/cmes.2019.04421

Abstract With the development of various navigation systems (such as GLONASS, Galileo, BDS), there is a sharp increase in the number of visible satellites. Accordingly, the probability of multiply gross measurements will increase. However, the conventional RAIM methods are difficult to meet the demands of the navigation system. In order to solve the problem of checking and identify multiple gross errors of receiver autonomous integrity monitoring (RAIM), this paper designed full matrix of single point positioning by QR decomposition, and proposed a new RAIM algorithm based on fuzzy clustering analysis with fuzzy c-means (FCM). And on More >

Jing Wang^1,*, Xiaohe Qiu¹, Yuanfei Tu¹

CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 227-244, 2019, DOI:10.32604/cmc.2019.05281

Abstract The MDS-MAP (multidimensional scaling-MAP) localization algorithm utilize almost merely connectivity information, and therefore it is easy to implement in practice of wireless sensor networks (WSNs). Anisotropic networks with energy hole, however, has blind communication spots that cause loss of information in the merging phase of MDSMAP. To enhance the positioning accuracy, the authors propose an MDS-MAP (CH) algorithm which can improve the clustering and merging strategy. In order to balance the effect of energy consumption and the network topology stabilization, we present a weighted clustering scheme, which considers the residual energy, the degree of connectivity More >

Assia Maamar^1,*, Khelifa Benahmed²

CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 15-39, 2019, DOI:10.32604/cmc.2019.06497

Abstract Recently, the radical digital transformation has deeply affected the traditional electricity grid and transformed it into an intelligent network (smart grid). This mutation is based on the progressive development of advanced technologies: advanced metering infrastructure (AMI) and smart meter which play a crucial role in the development of smart grid. AMI technologies have a promising potential in terms of improvement in energy efficiency, better demand management, and reduction in electricity costs. However the possibility of hacking smart meters and electricity theft is still among the most significant challenges facing electricity companies. In this regard, we… More >

Yongzheng Lin¹, Hong Liu^{1, ∗}, Zhenxiang Chen², Kun Zhang², Kun Ma²

CMC-Computers, Materials & Continua, Vol.60, No.1, pp. 245-257, 2019, DOI:10.32604/cmc.2019.04322

Abstract Process object is the instance of process. Vertexes and edges are in the graph of process object. There are different types of the object itself and the associations between object. For the large-scale data, there are many changes reflected. Recently, how to find appropriate real-time data for process object becomes a hot research topic. Data sampling is a kind of finding c hanges o f p rocess o bjects. There i s r equirements f or s ampling to be adaptive to underlying distribution of data stream. In this paper, we have proposed a adaptive More >

Yujie Zhang¹, Genlin Ji^1,*, Bin Zhao¹, Bo Sheng²

CMC-Computers, Materials & Continua, Vol.59, No.3, pp. 885-901, 2019, DOI:10.32604/cmc.2019.05612

Abstract The discovery of gradual moving object clusters pattern from trajectory streams allows characterizing movement behavior in real time environment, which leverages new applications and services. Since the trajectory streams is rapidly evolving, continuously created and cannot be stored indefinitely in memory, the existing approaches designed on static trajectory datasets are not suitable for discovering gradual moving object clusters pattern from trajectory streams. This paper proposes a novel algorithm of gradual moving object clusters pattern discovery from trajectory streams using sliding window models. By processing the trajectory data in current window, the mining algorithm can capture More >

Wentao Zhao¹, Pan Li^1,*, Chengzhang Zhu^1,2, Dan Liu¹, Xiao Liu¹

CMC-Computers, Materials & Continua, Vol.59, No.3, pp. 817-832, 2019, DOI:10.32604/cmc.2019.05957

Abstract The defense techniques for machine learning are critical yet challenging due to the number and type of attacks for widely applied machine learning algorithms are significantly increasing. Among these attacks, the poisoning attack, which disturbs machine learning algorithms by injecting poisoning samples, is an attack with the greatest threat. In this paper, we focus on analyzing the characteristics of positioning samples and propose a novel sample evaluation method to defend against the poisoning attack catering for the characteristics of poisoning samples. To capture the intrinsic data characteristics from heterogeneous aspects, we first evaluate training data More >