ABSTRACT Reliable prediction of sales can improve the quality of business strategy. This research... more ABSTRACT Reliable prediction of sales can improve the quality of business strategy. This research develops a hybrid model by integrating K-mean cluster and Back Propagation Network (KBPN) to forecast the future sales of a printed circuit board factory. Base on the K-mean clustering technique, the history data can be classified into different clusters, thus the noise of the original data can be reduced and a more accurate prediction model can be established. Numerical data of various affecting factors and actual demand of the past 5 years of the printed circuit board (PCB) factory are collected and input into the hybrid model for future monthly sales forecasting. Experimental results show the effectiveness of the hybrid model when comparing it with other approaches.
Proceedings of the 2009 International Conference on Hybrid Information Technology - ICHIT '09, 2009
ABSTRACT This paper proposes a hybrid system that is developed by evolving Fuzzy Case-Based Reaso... more ABSTRACT This paper proposes a hybrid system that is developed by evolving Fuzzy Case-Based Reasoning (FCBR) with Genetic Algorithm (GA), for reverse sales forecasting of returning books. FCBR systems have been successfully applied in several domains of artificial intelligence. However, in conventional FCBR method each factor has the same weight which means each one has the same influence on the output data that does not reflect the practical situation. In order to enhance the efficiency and capability of forecasting in FCBR systems, we connected the GAs method to adjust the weights of factors in FCBR systems, GAFCBR for short. The case base of this research is acquired from a book wholesaler in Taiwan, and it is applied by the hybrid system to forecast returning books. The results of the prediction of the hybrid system were compared with the results of a back propagation neural network (BPNN), a conventional CBR, and a multiple-regression analysis method. The experimental results show that the GAFCBR is more accurate and efficient when being applied to the forecast of the returning books than other methods.
Reliable prediction of sales can improve the quality of business strategy. Case-Based Reasoning (... more Reliable prediction of sales can improve the quality of business strategy. Case-Based Reasoning (CBR), one of the well known Artificial Intelligence (AI) techniques, has already proven its effectiveness in numerous studies. However, due to the uncertainties in knowledge representation, attribute description, and similarity measures in CBR, it's very difficult to find the similar cases from case bases. In order to deal with this problem, fuzzy theories have been incorporated into CBR allowing for more flexible and accurate models. This research develops a hybrid model by integrating Self Organization Map (SOM) neural network for data clustering, Genetic Algorithms (GAs) for parameters optimization and Weighted Fuzzy CBR (WFCBR) as main forecasting model to forecast the future sales in a printed circuit board (PCB) factory. This hybrid model encompasses two novel concepts: 1. Clustering WFCBR into different clusters by adopting SOM, thus the interaction between WFCBR is reduced an...
2009 International Conference on Management and Service Science, 2009
Drop-shipping is a rising channel operation model born in the environment of rapid development of... more Drop-shipping is a rising channel operation model born in the environment of rapid development of e-commerce and information technologies. According to drop-shipping model, retailers take charge of nothing but marketing and sales, while suppliers handle production and delivery. Retailer sales effort influences market demand and supplier's output, which finally determine the profit. In this paper, based on classic newsvendor model,
5th International Conference on Computer Sciences and Convergence Information Technology, 2010
ABSTRACT This research presents a Sub-Population Artificial Immune System (SPAIS) approach to sol... more ABSTRACT This research presents a Sub-Population Artificial Immune System (SPAIS) approach to solve the Multi-Objective Flowshop Scheduling Problems (MOFSP). We divide the populations in several sub-groups for different weighted objective functions. Than new AIS developed in this paper is incorporated after. In AIS field, most researchers use the clonal selection of B cells during the evolving processes to solve various optimization problems. Instead, we try to develop the T helper cell and T suppressor cell in T cell combining B cell to solve the MOFSP. Where T helper cell is used to help improving the solution and then T suppressor cell is generated to increase the diversity of the population. The total difference of completion time of each job is applied as the affinity function instead of the difference of makespan of the schedule. By integrate the subpopulation concept and the proposed AIS, both the diversity and the convergence can be concerned. This SPAIS method can supplement the flaw of SPGA using fitness as the basis and a new Lifespan which will keep good diversified chromosomes within the population to extend the searching spaces. The experimental tests show that this novel SPAIS method is very effective when comparing with SPGA [16], NSGA-II [10], and SPEA-II [3].
The aim of this paper is to study two new forms of genetic operators: duplication and fabrication... more The aim of this paper is to study two new forms of genetic operators: duplication and fabrication. Duplication is a reproduce procedure that will reproduce the best fit chromosome from the elite base. The introduction of duplication operator into the modified GA will speed up the convergence rate of the algorithm however the trap into local optimality can be avoided. Fabrication is an artificial procedure used to produce one or several chromosomes by mining gene structures from the elite chromosome base.
Abstract. In this paper, a hybrid system is developed by evolving Case-Based Reasoning (CBR) with... more Abstract. In this paper, a hybrid system is developed by evolving Case-Based Reasoning (CBR) with Genetic Algorithm (GA) for reverse sales forecasting of returning books. CBR systems have been successfully applied in several domains of artificial intelligence. However, in conventional CBR method each factor has the same weight which means each one has the same influence on the output data that does not reflect the practical situation.
Abstract This paper presents a novel memetic genetic algorithm (GA) for the flow shop scheduling ... more Abstract This paper presents a novel memetic genetic algorithm (GA) for the flow shop scheduling problem by combining mutation-based local search with traditional genetic algorithm. The local search is based on the depth-first mutation-based searching process and the depth, ie, the number of total mutation within each generation is according to the number of jobs to be scheduled.
2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009, 2009
Abstract Stock turning points detection is a very interesting subject arising in numerous financi... more Abstract Stock turning points detection is a very interesting subject arising in numerous financial and economic planning problems. In this paper, evolving neural network model with dynamic time warping piecewise linear representation system for stock turning points detection is presented. The piecewise linear representation method is able to generate numerous stocks turning points from the historic data base, then evolving neural network model will be applied to train the pattern and retrieve similar stock price patterns from ...
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2009
Abstract. Stock turning signals detection are very interesting subject arising in numerous financ... more Abstract. Stock turning signals detection are very interesting subject arising in numerous financial and economic planning problems. In this paper, Ensemble Neural Network system with Intelligent Piecewise Linear Representation for stock turning points detection is presented. The Intelligent piecewise linear representation method is able to generate numerous stocks turning signals from the historic data base, then Ensemble Neural Network system will be applied to train the pattern and retrieve similar stock price patterns from ...
Proceeding - 5th International Conference on Computer Sciences and Convergence Information Technology, ICCIT 2010, 2010
Abstract This research presents a two-stage AIS approach to solve the Grid scheduling problems. A... more Abstract This research presents a two-stage AIS approach to solve the Grid scheduling problems. According to the literature survey, most researchers use the clone selection of B cells during the evolving processes and the function of B cells in AIS researches to solve various optimization problems. Instead, we try to implement the T helper cell and T suppressor cell in T cell combining B cell to solve the Grid Scheduling problems. The major differences of our method from other earlier approaches includes: 1. A two-stage ...
Abstract An instrument based on twin laser sensors for non-contact measuring is designed for a ma... more Abstract An instrument based on twin laser sensors for non-contact measuring is designed for a machine tool applied in the process monitoring for the thickness measurement of a print circuit board (PCB). Without proper adjustments of an experienced operator, the precision of twin laser measuring is worse than the resolution of a single laser measuring.
ABSTRACT Reliable prediction of sales can improve the quality of business strategy. This research... more ABSTRACT Reliable prediction of sales can improve the quality of business strategy. This research develops a hybrid model by integrating K-mean cluster and Back Propagation Network (KBPN) to forecast the future sales of a printed circuit board factory. Base on the K-mean clustering technique, the history data can be classified into different clusters, thus the noise of the original data can be reduced and a more accurate prediction model can be established. Numerical data of various affecting factors and actual demand of the past 5 years of the printed circuit board (PCB) factory are collected and input into the hybrid model for future monthly sales forecasting. Experimental results show the effectiveness of the hybrid model when comparing it with other approaches.
Proceedings of the 2009 International Conference on Hybrid Information Technology - ICHIT '09, 2009
ABSTRACT This paper proposes a hybrid system that is developed by evolving Fuzzy Case-Based Reaso... more ABSTRACT This paper proposes a hybrid system that is developed by evolving Fuzzy Case-Based Reasoning (FCBR) with Genetic Algorithm (GA), for reverse sales forecasting of returning books. FCBR systems have been successfully applied in several domains of artificial intelligence. However, in conventional FCBR method each factor has the same weight which means each one has the same influence on the output data that does not reflect the practical situation. In order to enhance the efficiency and capability of forecasting in FCBR systems, we connected the GAs method to adjust the weights of factors in FCBR systems, GAFCBR for short. The case base of this research is acquired from a book wholesaler in Taiwan, and it is applied by the hybrid system to forecast returning books. The results of the prediction of the hybrid system were compared with the results of a back propagation neural network (BPNN), a conventional CBR, and a multiple-regression analysis method. The experimental results show that the GAFCBR is more accurate and efficient when being applied to the forecast of the returning books than other methods.
Reliable prediction of sales can improve the quality of business strategy. Case-Based Reasoning (... more Reliable prediction of sales can improve the quality of business strategy. Case-Based Reasoning (CBR), one of the well known Artificial Intelligence (AI) techniques, has already proven its effectiveness in numerous studies. However, due to the uncertainties in knowledge representation, attribute description, and similarity measures in CBR, it's very difficult to find the similar cases from case bases. In order to deal with this problem, fuzzy theories have been incorporated into CBR allowing for more flexible and accurate models. This research develops a hybrid model by integrating Self Organization Map (SOM) neural network for data clustering, Genetic Algorithms (GAs) for parameters optimization and Weighted Fuzzy CBR (WFCBR) as main forecasting model to forecast the future sales in a printed circuit board (PCB) factory. This hybrid model encompasses two novel concepts: 1. Clustering WFCBR into different clusters by adopting SOM, thus the interaction between WFCBR is reduced an...
2009 International Conference on Management and Service Science, 2009
Drop-shipping is a rising channel operation model born in the environment of rapid development of... more Drop-shipping is a rising channel operation model born in the environment of rapid development of e-commerce and information technologies. According to drop-shipping model, retailers take charge of nothing but marketing and sales, while suppliers handle production and delivery. Retailer sales effort influences market demand and supplier's output, which finally determine the profit. In this paper, based on classic newsvendor model,
5th International Conference on Computer Sciences and Convergence Information Technology, 2010
ABSTRACT This research presents a Sub-Population Artificial Immune System (SPAIS) approach to sol... more ABSTRACT This research presents a Sub-Population Artificial Immune System (SPAIS) approach to solve the Multi-Objective Flowshop Scheduling Problems (MOFSP). We divide the populations in several sub-groups for different weighted objective functions. Than new AIS developed in this paper is incorporated after. In AIS field, most researchers use the clonal selection of B cells during the evolving processes to solve various optimization problems. Instead, we try to develop the T helper cell and T suppressor cell in T cell combining B cell to solve the MOFSP. Where T helper cell is used to help improving the solution and then T suppressor cell is generated to increase the diversity of the population. The total difference of completion time of each job is applied as the affinity function instead of the difference of makespan of the schedule. By integrate the subpopulation concept and the proposed AIS, both the diversity and the convergence can be concerned. This SPAIS method can supplement the flaw of SPGA using fitness as the basis and a new Lifespan which will keep good diversified chromosomes within the population to extend the searching spaces. The experimental tests show that this novel SPAIS method is very effective when comparing with SPGA [16], NSGA-II [10], and SPEA-II [3].
The aim of this paper is to study two new forms of genetic operators: duplication and fabrication... more The aim of this paper is to study two new forms of genetic operators: duplication and fabrication. Duplication is a reproduce procedure that will reproduce the best fit chromosome from the elite base. The introduction of duplication operator into the modified GA will speed up the convergence rate of the algorithm however the trap into local optimality can be avoided. Fabrication is an artificial procedure used to produce one or several chromosomes by mining gene structures from the elite chromosome base.
Abstract. In this paper, a hybrid system is developed by evolving Case-Based Reasoning (CBR) with... more Abstract. In this paper, a hybrid system is developed by evolving Case-Based Reasoning (CBR) with Genetic Algorithm (GA) for reverse sales forecasting of returning books. CBR systems have been successfully applied in several domains of artificial intelligence. However, in conventional CBR method each factor has the same weight which means each one has the same influence on the output data that does not reflect the practical situation.
Abstract This paper presents a novel memetic genetic algorithm (GA) for the flow shop scheduling ... more Abstract This paper presents a novel memetic genetic algorithm (GA) for the flow shop scheduling problem by combining mutation-based local search with traditional genetic algorithm. The local search is based on the depth-first mutation-based searching process and the depth, ie, the number of total mutation within each generation is according to the number of jobs to be scheduled.
2009 WRI World Congress on Computer Science and Information Engineering, CSIE 2009, 2009
Abstract Stock turning points detection is a very interesting subject arising in numerous financi... more Abstract Stock turning points detection is a very interesting subject arising in numerous financial and economic planning problems. In this paper, evolving neural network model with dynamic time warping piecewise linear representation system for stock turning points detection is presented. The piecewise linear representation method is able to generate numerous stocks turning points from the historic data base, then evolving neural network model will be applied to train the pattern and retrieve similar stock price patterns from ...
Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics), 2009
Abstract. Stock turning signals detection are very interesting subject arising in numerous financ... more Abstract. Stock turning signals detection are very interesting subject arising in numerous financial and economic planning problems. In this paper, Ensemble Neural Network system with Intelligent Piecewise Linear Representation for stock turning points detection is presented. The Intelligent piecewise linear representation method is able to generate numerous stocks turning signals from the historic data base, then Ensemble Neural Network system will be applied to train the pattern and retrieve similar stock price patterns from ...
Proceeding - 5th International Conference on Computer Sciences and Convergence Information Technology, ICCIT 2010, 2010
Abstract This research presents a two-stage AIS approach to solve the Grid scheduling problems. A... more Abstract This research presents a two-stage AIS approach to solve the Grid scheduling problems. According to the literature survey, most researchers use the clone selection of B cells during the evolving processes and the function of B cells in AIS researches to solve various optimization problems. Instead, we try to implement the T helper cell and T suppressor cell in T cell combining B cell to solve the Grid Scheduling problems. The major differences of our method from other earlier approaches includes: 1. A two-stage ...
Abstract An instrument based on twin laser sensors for non-contact measuring is designed for a ma... more Abstract An instrument based on twin laser sensors for non-contact measuring is designed for a machine tool applied in the process monitoring for the thickness measurement of a print circuit board (PCB). Without proper adjustments of an experienced operator, the precision of twin laser measuring is worse than the resolution of a single laser measuring.
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Papers by Chen-hao Liu