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Harmonic Path Planning using Two-Stage Half- Sweep Arithmetic Mean Method 两段半扫算术平均法的谐波路径规划
Journal of Computer Science & Computational Mathematics Pub Date : 2019-06-30 DOI: 10.20967/JCSCM.2019.02.002
A. Saudi, J. Sulaiman
{"title":"Harmonic Path Planning using Two-Stage Half- Sweep Arithmetic Mean Method","authors":"A. Saudi, J. Sulaiman","doi":"10.20967/JCSCM.2019.02.002","DOIUrl":"https://doi.org/10.20967/JCSCM.2019.02.002","url":null,"abstract":"This paper presents the application of a two-stage HalfSweep Arithmetic Mean (HSAM) iterative method for computing the solution of Laplace's equation (also known as harmonic functions) in two-dimensional space to solve the path planning problem in indoor environment. Several path planning simulations in a known indoor environment were conducted to examine the effectiveness of the proposed method. It is shown that the designed path planning algorithm is capable of generating smooth paths from various start and goal positions. Also, numerical results show that the proposed HSAM method converges much faster than the existing iterative methods, thus it drastically improves the overall performance of the path planning algorithm.","PeriodicalId":374608,"journal":{"name":"Journal of Computer Science & Computational Mathematics","volume":"53 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126090984","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: 2
Mapping Properties of Mixed Fractional Differentiation Operators in Hölder Spaces Defined by Usual Hölder Condition 通常Hölder条件下Hölder空间中混合分数阶微分算子的映射性质
Journal of Computer Science & Computational Mathematics Pub Date : 2019-06-30 DOI: 10.20967/JCSCM.2019.02.003
T. Mamatov
{"title":"Mapping Properties of Mixed Fractional Differentiation Operators in Hölder Spaces Defined by Usual Hölder Condition","authors":"T. Mamatov","doi":"10.20967/JCSCM.2019.02.003","DOIUrl":"https://doi.org/10.20967/JCSCM.2019.02.003","url":null,"abstract":"We study mixed fractional derivative in Marchaud form of function of two variables in Hölder spaces of different orders in each variables. We consider Hölder spaces defined both by first order differences in each variable and also by the mixed second order difference, the main interest being in the evaluation of the latter for the mixed fractional derivative in the cases Hölder class.","PeriodicalId":374608,"journal":{"name":"Journal of Computer Science & Computational Mathematics","volume":"37 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"126341005","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: 2
Smarandache Curves According to the Extended Darboux Frame in Euclidean 4-Space 欧几里得4空间中扩展达布坐标系下的Smarandache曲线
Journal of Computer Science & Computational Mathematics Pub Date : 2019-06-30 DOI: 10.20967/JCSCM.2019.02.001
Bahar Uyar Düldül
{"title":"Smarandache Curves According to the Extended Darboux Frame in Euclidean 4-Space","authors":"Bahar Uyar Düldül","doi":"10.20967/JCSCM.2019.02.001","DOIUrl":"https://doi.org/10.20967/JCSCM.2019.02.001","url":null,"abstract":"In this paper, considering the extended Darboux frame in Euclidean 4-space, we define some special Smarandache curves. We calculate the Frenet apparatus of these curves depending on the invariants of the extended Darboux frame of second kind.","PeriodicalId":374608,"journal":{"name":"Journal of Computer Science & Computational Mathematics","volume":"56 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-06-30","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"129927821","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: 5
Modelling Annual Maximum River Flows with Generalized Extreme Value Distribution 用广义极值分布模拟年最大河流流量
Journal of Computer Science & Computational Mathematics Pub Date : 2019-03-31 DOI: 10.20967/JCSCM.2019.01.002
R. Y. Cheong, D. Gabda
{"title":"Modelling Annual Maximum River Flows with Generalized Extreme Value Distribution","authors":"R. Y. Cheong, D. Gabda","doi":"10.20967/JCSCM.2019.01.002","DOIUrl":"https://doi.org/10.20967/JCSCM.2019.01.002","url":null,"abstract":"A good understanding of probability distribution of annual maximum river flow is believed to improve water resources planning and design. Based on the annual maximum river flow record over 20-48 years at 9 individual river sites in Sabah, the data set are fitted into generalized extreme value (GEV) distribution with maximum likelihood estimator. Both stationary and non-stationary models are considered. Likelihood ratio test shows that most of the river flows are stationary. Over a homogeneous region, a parent distribution with common shape parameter is found well describing the behaviour of selected annual maximum river flow. Hence, 10and 100-year return levels are estimated using the single model.","PeriodicalId":374608,"journal":{"name":"Journal of Computer Science & Computational Mathematics","volume":"47 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127215157","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: 0
Handshape Recognition Using Correlation Filter and Euclidean Distance 基于相关滤波和欧氏距离的手型识别
Journal of Computer Science & Computational Mathematics Pub Date : 2019-03-31 DOI: 10.20967/JCSCM.2019.01.003
W. Zailah, M. I. Solihin, W. Lee.S., Ang. C.K.
{"title":"Handshape Recognition Using Correlation Filter and Euclidean Distance","authors":"W. Zailah, M. I. Solihin, W. Lee.S., Ang. C.K.","doi":"10.20967/JCSCM.2019.01.003","DOIUrl":"https://doi.org/10.20967/JCSCM.2019.01.003","url":null,"abstract":"This paper proposes a handshape recognition based on correlation filter and Euclidean distance. Unlike biometric and face verification system, handshape is rarely used for verification of an individual. Therefore, handshape will be used as an alternative way for human identification and authentication for this system. The performance for the minimum average correlation energy (MACE) filter and Euclidean distance are evaluated using a new database.","PeriodicalId":374608,"journal":{"name":"Journal of Computer Science & Computational Mathematics","volume":"22 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"132709524","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: 0
A Study on Frequent Itemset Mining for Identifying Associated Multiple SNPs 关联多snp频繁项集挖掘研究
Journal of Computer Science & Computational Mathematics Pub Date : 2019-03-31 DOI: 10.20967/JCSCM.2019.01.001
S. Mutalib, A. Mohamed, S. Abdul-Rahman
{"title":"A Study on Frequent Itemset Mining for Identifying Associated Multiple SNPs","authors":"S. Mutalib, A. Mohamed, S. Abdul-Rahman","doi":"10.20967/JCSCM.2019.01.001","DOIUrl":"https://doi.org/10.20967/JCSCM.2019.01.001","url":null,"abstract":"Genome-wide association studies (GWAS) have gained a lot of interest in public health research to investigate the correlations of genetic variants and traits. Mostly, GWAS use standard statistical tests for each genetic variant to capture main genetic effects. Machine learning and data mining approaches are also promising enough to complement single and multiple genetic variants in understanding the general association of complex human disease. This paper explores a data mining approach to discover patterns of multiple genetic variants associated with a disease. Frequent itemset mining method was applied and the intersection algorithm in a row enumeration strategy was chosen to discover itemsets from genetic variants, which is known as Single Nucleotide Polymorphism (SNP). We chose the intersection algorithm because it is more suitable to mine high dimensional and sparse dataset. The found itemsets could be used by scientists to study associated with multiple genes in multifactorial disease.","PeriodicalId":374608,"journal":{"name":"Journal of Computer Science & Computational Mathematics","volume":"78 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2019-03-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"128296381","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: 2
Fuzzy Time Series Forecasting Model based on Centre of Gravity Similarity Measure 基于重心相似性测度的模糊时间序列预测模型
Journal of Computer Science & Computational Mathematics Pub Date : 2018-12-31 DOI: 10.20967/JCSCM.2018.04.010
N. Ramli, Siti Musleha Ab Mutalib, D. Mohamad
{"title":"Fuzzy Time Series Forecasting Model based on Centre of Gravity Similarity Measure","authors":"N. Ramli, Siti Musleha Ab Mutalib, D. Mohamad","doi":"10.20967/JCSCM.2018.04.010","DOIUrl":"https://doi.org/10.20967/JCSCM.2018.04.010","url":null,"abstract":"This paper proposes a new method for measuring fuzzy forecasting accuracy (FFA) based on centre of gravity (COG) similarity measure approach. Fuzzy time series (FTS) data represented in trapezoidal fuzzy numbers (TrFNs) form, average based length partitioning method, and first order fuzzy logical relation are used in developing the FTS forecasting model. The COG similarity measure is calculated between the fuzzified historical data and fuzzy forecasted values. The distance of COG similarity measure represents the error of the forecasting model which is the uniqueness of the FFA method. The proposed forecasting model is applied in a numerical example of unemployment rate with the forecasting error of 0.0241 obtained. The new FFA can be directly obtained from the fuzzy forecasted values without going through the defuzzification process as compared to other fuzzy forecasting models. The historical data and forecasted values remained in the TrFNs form and, thus, this proposed forecasting model preserved the information that has been kept during the forecasting procedure from being lost. The proposed model can be applied in other time series data such as forecasts on finance, tourism and weather.","PeriodicalId":374608,"journal":{"name":"Journal of Computer Science & Computational Mathematics","volume":"2 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123907619","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: 4
Capacity Allocation Optimization using Offline Learning Differential Evolution Hyper-Heuristic 基于离线学习差分进化超启发式的容量分配优化
Journal of Computer Science & Computational Mathematics Pub Date : 2018-12-31 DOI: 10.20967/JCSCM.2018.04.002
Mohamad Fiqri, Chin Jeng Feng
{"title":"Capacity Allocation Optimization using Offline Learning Differential Evolution Hyper-Heuristic","authors":"Mohamad Fiqri, Chin Jeng Feng","doi":"10.20967/JCSCM.2018.04.002","DOIUrl":"https://doi.org/10.20967/JCSCM.2018.04.002","url":null,"abstract":"Hyper-heuristics are high-level computational techniques to select or generate heuristics for solving complex problems, such as capacity planning involving finite resource allocation. This research proposes a hyper-heuristics method based on two-level differential evolution (DE) termed as HMDE. It optimizes four parameters in the hyper stage, namely mutation factor, crossover rate, number of generations, and number of iterations to derive a comparatively superior capacity planning meta-heuristics, also in the form of DE. The effect of demand seasonality onto its performance is examined and benchmarked against Genetic Algorithm (GA). As it is statistically proven from the results, HMDE has shortened the runtime and produced higher profit on average in comparison to the GA over a test case containing twelve months of seasonal data.","PeriodicalId":374608,"journal":{"name":"Journal of Computer Science & Computational Mathematics","volume":"26 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"127017777","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: 0
Weighted Sum-Dijkstra's Algorithm in Best Path Identification based on Multiple Criteria 基于多准则的加权Sum-Dijkstra最优路径识别算法
Journal of Computer Science & Computational Mathematics Pub Date : 2018-12-31 DOI: 10.20967/JCSCM.2018.04.008
Ting Hua, N. Abdullah
{"title":"Weighted Sum-Dijkstra's Algorithm in Best Path Identification based on Multiple Criteria","authors":"Ting Hua, N. Abdullah","doi":"10.20967/JCSCM.2018.04.008","DOIUrl":"https://doi.org/10.20967/JCSCM.2018.04.008","url":null,"abstract":"People faced decision making in choosing a suitable path for their own preferences. Usually, more than one criterion is involved in order to match with the preferences of the decision makers. The main objective of this paper was to identify the best path selection based on multiple criteria instead of a single criterion. Dijkstra’s Algorithm is a shortest path algorithm that considers a single criterion only. Weighted Sum Method (WSM) is one of the weighting methods to solve the multi criteria decision making problems (MCDM). In order to achieve the objective, Weighted Sum-Dijkstra’s Algorithm (WSDA), a combination method between WSM and Dijkstra’s Algorithm is applied to solve multiple criteria network problems. In this paper, Dijkstra’s Algorithm and WSM are reviewed and compared as to the WSDA. In addition, two examples with equal criteria values to evaluate the performances of the approach are presented. Results show that WSDA performed better in terms of the criteria concerned as it was compared to the Dijkstra’s algorithm. Moreover, the results could be directly found without considering all the alternative paths of the problem. WSDA can be user friendly to users from non-mathematical background. It is not only applicable to urban road problems, but other network problems such as pipelines and bandwidth network problems. When come to large scale data problems, Maple software is used to solve it with ease.","PeriodicalId":374608,"journal":{"name":"Journal of Computer Science & Computational Mathematics","volume":"10 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"123641982","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: 9
Numerical Assessment of Anisotropic Diffusion Equation for Image Blurring Using SOR Iteration 基于SOR迭代的图像模糊各向异性扩散方程数值评估
Journal of Computer Science & Computational Mathematics Pub Date : 2018-12-31 DOI: 10.20967/JCSCM.2018.04.009
N A Basran, J. Eng, A. Saudi, J. Sulaiman
{"title":"Numerical Assessment of Anisotropic Diffusion Equation for Image Blurring Using SOR Iteration","authors":"N A Basran, J. Eng, A. Saudi, J. Sulaiman","doi":"10.20967/JCSCM.2018.04.009","DOIUrl":"https://doi.org/10.20967/JCSCM.2018.04.009","url":null,"abstract":"Blurring the image while preserving the important features such as edges is a crucial study in computer vision. This paper presents the results of applying three iterative methods which are Jacobi, Gauss Seidel and Successive Overrelaxation (SOR) to solve anisotropic diffusion equation for image blurring, where the output image of Jacobi is used as a control image. The number of iterations and computational time required to solve the anisotropic diffusion equation are used to measure the performance of the considered iterative methods. The findings show that SOR method is more efficient to smooth the inner region of an image compared to Jacobi and Gauss-Seidel methods in which the SOR required the least number of iterations and computational time.","PeriodicalId":374608,"journal":{"name":"Journal of Computer Science & Computational Mathematics","volume":"1 1","pages":"0"},"PeriodicalIF":0.0,"publicationDate":"2018-12-31","publicationTypes":"Journal Article","fieldsOfStudy":null,"isOpenAccess":false,"openAccessPdf":"","citationCount":null,"resultStr":null,"platform":"Semanticscholar","paperid":"130173934","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: 0
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