Motivated by the business model called“community group buying”(CGB),which has emerged in China and some countries in Southeast Asia,such as Singapore and Indonesia,we develop algorithms that could help CGB platforms...Motivated by the business model called“community group buying”(CGB),which has emerged in China and some countries in Southeast Asia,such as Singapore and Indonesia,we develop algorithms that could help CGB platforms match consumers with stage-stations(the picking up center under the CGB mode).By altering the fundamental design of the existing hierarchy algorithms,improvements are achieved.It is proven that our method has a faster running speed and greater space efficiency.Our algorithms avoid traversal and compress the time complexities of matching a consumer with a stage-station and updating the storage information to O(logM)and O(MlogG),where M is the number of stage-stations and G is that of the platform’s stock-keeping units.Simulation comparisons of our algorithms with the current methods of CGB platforms show that our approaches can effectively reduce delivery costs.An interesting observation of the simula-tions is worthy of note:Increasing G may incur higher costs since it makes inventories more dispersed and delivery prob-lems more complicated.展开更多
As the traditional non-linear systems generally based on gradient descent optimization method have some shortage in the field of groundwater level prediction, the paper, according to structure, algorithm and shortcomi...As the traditional non-linear systems generally based on gradient descent optimization method have some shortage in the field of groundwater level prediction, the paper, according to structure, algorithm and shortcoming of the conventional radial basis function neural network （RBF NN）, presented a new improved genetic algorithm （GA）： hybrid hierarchy genetic algorithm （HHGA）. In training RBF NN, the algorithm can automatically determine the structure and parameters of RBF based on the given sample data. Compared with the traditional groundwater level prediction model based on back propagation （BP） or RBF NN, the new prediction model based on HHGA and RBF NN can greatly increase the convergence speed and precision.展开更多
Based on experimental data of line heating, the methods of vector mapping, plane projection, and coordinate converting are presented to establish the spectra for line heating distortion discipline which shows the rela...Based on experimental data of line heating, the methods of vector mapping, plane projection, and coordinate converting are presented to establish the spectra for line heating distortion discipline which shows the relationship between process parameters and distortion parameters of line heating. Back-propagation network （BP-net） is used to modify tile spectra. Mathematical models for optimizing line heating techniques parameters, which include two-objective functions, are constructed. To convert the multi-objective optimization into a single-objective one, the method of changifig weight coefficient is used, and then the individual fitness function is built up, Taking the number of heating lines, distance between the heating lines＇ border （line space）, and shrink quantity of lines as three restrictive conditions, a hierarchy genetic algorithm （HGA） code is established by making use of information provided by the spectra, in which inner coding and outer coding adopt different heredity arithmetic operators in inherent operating, The numerical example shows that the spectra for line heating distortion discipline presented here can provide accurate information required by techniques parameter prediction of line heating process and the technique parameter optimization method based on HGA provided here can obtain good results for hull plate.展开更多
Presumptive identifcation of different Enterobaeteriaeeae species is routinely achieved based on biochemical properties. Traditional practice includes manual comparison of each biochem- ical property of the unknown sa...Presumptive identifcation of different Enterobaeteriaeeae species is routinely achieved based on biochemical properties. Traditional practice includes manual comparison of each biochem- ical property of the unknown sample with known reference samples and inference of its identity based on the maximum similarity pattern with the known samples. This process is labor- intensive, time-consuming, error-prone, and subjective. Therefore, automation of sorting and sim- ilarity in calculation would be advantageous. Here we present a MATLAB-based graphical user interface （GUI） tool named BioCluster. This tool was designed for automated clustering and iden- tification of Enterobacteriaceae based on biochemical test results. In this tool, we used two types of algorithms, i.e., traditional hierarchical clustering （HC） and the Improved Hierarchical Clustering （IHC）, a modified algorithm that was developed specifically for the clustering and identification of within this species. IHC takes into account the variability in result of 1-47 biochemical tests family. This tool also provides different options to optimize the clus- tering in a user-friendly way. Using computer-generated synthetic data and some real data, we have demonstrated that BioCluster has high accuracy in clustering and identifying enterobacterial species based on biochemical test data. This tool can be freely downloaded at http：//microbialgen.du.ac.bd/ biocluster/.展开更多
基金supported by the National Natural Science Foundation of China(71991464,71921001)Fundamental Research Funds for the Central Universities,General Program(WK2040000053)Key Program(YD2040002027)。
文摘Motivated by the business model called“community group buying”(CGB),which has emerged in China and some countries in Southeast Asia,such as Singapore and Indonesia,we develop algorithms that could help CGB platforms match consumers with stage-stations(the picking up center under the CGB mode).By altering the fundamental design of the existing hierarchy algorithms,improvements are achieved.It is proven that our method has a faster running speed and greater space efficiency.Our algorithms avoid traversal and compress the time complexities of matching a consumer with a stage-station and updating the storage information to O(logM)and O(MlogG),where M is the number of stage-stations and G is that of the platform’s stock-keeping units.Simulation comparisons of our algorithms with the current methods of CGB platforms show that our approaches can effectively reduce delivery costs.An interesting observation of the simula-tions is worthy of note:Increasing G may incur higher costs since it makes inventories more dispersed and delivery prob-lems more complicated.
文摘As the traditional non-linear systems generally based on gradient descent optimization method have some shortage in the field of groundwater level prediction, the paper, according to structure, algorithm and shortcoming of the conventional radial basis function neural network （RBF NN）, presented a new improved genetic algorithm （GA）： hybrid hierarchy genetic algorithm （HHGA）. In training RBF NN, the algorithm can automatically determine the structure and parameters of RBF based on the given sample data. Compared with the traditional groundwater level prediction model based on back propagation （BP） or RBF NN, the new prediction model based on HHGA and RBF NN can greatly increase the convergence speed and precision.
文摘Based on experimental data of line heating, the methods of vector mapping, plane projection, and coordinate converting are presented to establish the spectra for line heating distortion discipline which shows the relationship between process parameters and distortion parameters of line heating. Back-propagation network （BP-net） is used to modify tile spectra. Mathematical models for optimizing line heating techniques parameters, which include two-objective functions, are constructed. To convert the multi-objective optimization into a single-objective one, the method of changifig weight coefficient is used, and then the individual fitness function is built up, Taking the number of heating lines, distance between the heating lines＇ border （line space）, and shrink quantity of lines as three restrictive conditions, a hierarchy genetic algorithm （HGA） code is established by making use of information provided by the spectra, in which inner coding and outer coding adopt different heredity arithmetic operators in inherent operating, The numerical example shows that the spectra for line heating distortion discipline presented here can provide accurate information required by techniques parameter prediction of line heating process and the technique parameter optimization method based on HGA provided here can obtain good results for hull plate.
基金supported by the grants from the Ministry of Science and Technology (S&T) of Bangladesh (Grant No.HEQEP CP236)the University Grants Commission (UGC).
文摘Presumptive identifcation of different Enterobaeteriaeeae species is routinely achieved based on biochemical properties. Traditional practice includes manual comparison of each biochem- ical property of the unknown sample with known reference samples and inference of its identity based on the maximum similarity pattern with the known samples. This process is labor- intensive, time-consuming, error-prone, and subjective. Therefore, automation of sorting and sim- ilarity in calculation would be advantageous. Here we present a MATLAB-based graphical user interface （GUI） tool named BioCluster. This tool was designed for automated clustering and iden- tification of Enterobacteriaceae based on biochemical test results. In this tool, we used two types of algorithms, i.e., traditional hierarchical clustering （HC） and the Improved Hierarchical Clustering （IHC）, a modified algorithm that was developed specifically for the clustering and identification of within this species. IHC takes into account the variability in result of 1-47 biochemical tests family. This tool also provides different options to optimize the clus- tering in a user-friendly way. Using computer-generated synthetic data and some real data, we have demonstrated that BioCluster has high accuracy in clustering and identifying enterobacterial species based on biochemical test data. This tool can be freely downloaded at http：//microbialgen.du.ac.bd/ biocluster/.
