The Infona portal uses cookies, i.e. strings of text saved by a browser on the user's device. The portal can access those files and use them to remember the user's data, such as their chosen settings (screen view, interface language, etc.), or their login data. By using the Infona portal the user accepts automatic saving and using this information for portal operation purposes. More information on the subject can be found in the Privacy Policy and Terms of Service. By closing this window the user confirms that they have read the information on cookie usage, and they accept the privacy policy and the way cookies are used by the portal. You can change the cookie settings in your browser.
Using genetic algorithm and BP neural network method of combining, this paper has established dynamic forward feedback correction model and has completed the automatic adjustment of the various parameters required for rolling steel pipe, and has made rolled steel pipe system work at the best value. After the actual data validation, the model can more accurately pre-adjusted parameters to achieve intelligent...
Forecasting cash flow objectively is very important in discounted cash flow analysis. In order to predict cash flow after mergers, this paper puts forward a model based on genetic-algorithm and BP neural network, designs the steps of algorithm, build the structure of BP neural network. By simulation of data, the result indicates the model has good performance of prediction. It can overcome the flaws...
In order to overcome the shortcomings of BP neural network, the golden section theory was used to get the reasonable number of Back Propagation (BP) neural network's hidden nodes. By using Genetic Algorithm (GA) to optimize the initial weights and threshold value of BP neural network, the network converged quickly and the recognition precision was increased. The GA-BP neural network model was utilized...
Although simple genetic algorithm (SGA) can, to some extent, improve the back propagation neural network (BP), it is prone to prematurity and losing the optimal solutions. Niche technology and fuzzy control theory are introduced to improve SGA and the improved one is used to optimize BP. The improved genetic algorithm is used to optimize BP neural network. In addition, due to the increasingly voltage...
This paper discusses the research works on the KICK skill from the view of fuzzy logic, genetic algorithms and BP neural network. It presents the different algorithms features used in the robotic soccer. Some of the improving algorithms are also proposed.
When exploring identification of coal and waste rock, 17 characteristic parameters of gray-scale histogram and gray level co-occurrence matrix (GLCM) were chosen according to their differences in gray scale and texture. Then, the principal component analysis (PCA) algorithm was used to get principal components from all the parameters chosen above. The principal components were defined as the inputs...
In allusion to the defects of the slow convergence speed and the local minimum for traditional BP algorithm, a new algorithm is proposed. The new algorithm is designed by hierarchical genetic algorithm together with the algorithm of automatically adjusting the S form function, which combines with the BP network to improve the efficiency of fault detection. With calculation and simulation, compared...
In order to more accurately predict industrial emissions, the paper selected BP and GA-BP neural network to establish the prediction model between the foreign trade and industrial waste discharge. Compared of different forecasting methods and examples of analysis of results, it shows that GA-BP neural network had higher accuracy, tolerant and excellent generalization ability than other model on ecology...
Component proportion sometimes is necessary in order to evaluate the state of research objects quantitatively or to do some specific studies. Back propagation neural network (BPNN) is one of mostly used neural networks because of its ability to achieve a high precision simulation for data problem or target function which is hardly to be established by conventional mathematical theory. In this paper,...
Two different Approaches are used to Optimize Lemon Grass Oil Production. Oil Production is compared and Production-Nutrient ratio comparison also shows that Logistic function is giving best result for production-nutrient ratio. So logistic Function proved to be better for optimizing results in our case.
Methods for the identification of temperature in intelligent building and building equipments is one of hot topics focused by lots of researchers in that research area. To implement the process of inspecting and forecasting of energy efficiency in building and its accessory, a feed forward neural network is used as the identification structure for temperature identification of internal space in building...
In order to design the products that meet consumer emotional demands, this paper proposes a systematic method which combines neural network with genetic algorithm. Firstly, a back propagation neural network is applied to map the relationships between product design elements and customer kansei image evaluation. Secondly, generic algorithm is employed to search for the optimal product form which satisfies...
Yield is a very important criterion to measure the semiconductor wafer fabrication facilities (FABs) productivity. The finished products will be check by Wafer Acceptance Test (WAT) and Circuit Probe (CP) to classified into ferior goods or inferior goods. This research applied the data from WAT and CP for the selection of the most important measuring parameters to improve the yield. Three methods,...
Active Queue Management (AQM) has been widely used for congestion avoidance in TCP networks. Although numerous AQM schemes have been proposed to regulate a queue size close to a reference level as RED, PI controller, PID Controller, Adaptive prediction controller (APC) and neural network using the Back-Propagation (BP) most of them are incapable of adequately adapting to TCP network dynamics due to...
This paper presents a grey predictive control method for a class of nonlinear systems with unknown input delay. By using BP neural network, the unknown input delay is identified firstly. The system output is then estimated by the grey predictive algorithm. The output feedback control is fulfilled by PID algorithm which is used to tune its three parameters. By means of combining grey predictive algorithm...
Research on production scheduling under uncertainty has recently received much attention. This paper presents a novel decomposition-based approach (DBA) to flexible flow shop (FFS) scheduling under stochastic setup times. In comparison with traditional methods using a single approach, the proposed DBA combines and takes advantage of two different approaches, namely the Genetic Algorithm (GA) and the...
The robustness problem in the aircraft design optimization is discussed in reference to the undulation of aircraft performance derived from uncertainty factors. A new robust design optimization (RDO) model, the constrained condition method (CCM), is expounded perspicuously. By dint of genetic algorithm (GA) joining with Back Propagation neural networks response surface (BP-NNRS), two optimal schemes,...
As genetic algorithm can't maintain the diversity of groups and is prone to prematurity, in this paper one introduce niche technology and fuzzy control theory to improve the simple genetic algorithm. The niche technology preserve the variety of the population and fuzzy control can make sure GA gets the optimal solutions in the global search by controlling the crossover- probability and mutation-probability...
A hybrid algorithm -RFN network of self-adaptive genetic algorithm was introduced, which combined the excellences of BP network, RFN network and genetic algorithm. The hybrid algorithm adopts the learning rule of RFN network and combines self-adaptive genetic algorithm and gradient descent method. The capability of prediction can be optimized using the hybrid algorithm and the shortcoming of the learning...
Early-warning system of China's real estate is still in the development of a sound stage, and there are following two main aspects. Firstly, the selection of indicators is to be improved. Secondly, predictive capability of the turning point about the real estate business cycle is to be improved. Based on the above-mentioned problems, the Rough-GA-BP model proposed is applied to the real estate early-warning...
Set the date range to filter the displayed results. You can set a starting date, ending date or both. You can enter the dates manually or choose them from the calendar.