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252. A morphological, anatomical and isozyme study of Potamogeton ×schreberi: confirmation of its recent occurrence in Germany and first documented record in France
- Creator:
- Kaplan , Zdeněk and Wolff , Peter
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- anatomy, clone, dispersal, distribution, electrophoresis, France, Germany, hybridization, isozymes, morphology, Potamogeton, relic, taxonomy, and vegetative propagation
- Language:
- English
- Description:
- A combined study of morphology, stem anatomy and isozyme patterns was used to reveal the identity of sterile plants from two rivers on the Germany/France border. A detailed morphological examination proved that the putative hybrid is clearly intermediate between Potamogeton natans and P. nodosus. The stem anatomy had characteristics of both species. The most compelling evidence came from the isozyme analysis. The additive “hybrid” banding patterns of the six enzyme systems studied indicate inheritance from P. natans and P. nodosus. In contrast, other morphologically similar hybrids were excluded: P. ×gessnacensis (= P. natans × P. polygonifolius) by all the enzyme systems, P. ×fluitans (= P. lucens × P. natans) by AAT, EST and 6PGDH, and P. ×sparganiifolius (= P. gramineus × P. natans) by AAT and EST. All samples of P. ×schreberi are of a single multi-enzyme phenotype, suggesting that they resulted from a single hybridization event and that the present-day distribution of P. ×schreberi along the Saarland/Moselle border was achieved by means of vegetative propagation and long-distance dispersal. Neither of its parental species occur with P. ×schreberi or are present upstream, which suggests that this hybrid has persisted vegetatively for a long time in the absence of its parents. The total distribution of this hybrid is reviewed and a detailed account of the records from Germany is given. P. ×schreberi appears to be a rare hybrid. The risk of incorrect determination resulting from the identification of insufficiently developed or inadequately preserved plant material is discussed.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public
253. A multi agent community of practice
- Creator:
- Peyravi, Farzad, Pashaei, Kaveh, and Taghiyareh, Fattaneh
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- Community of practice, Multi-agent system, Mas-CommonKADS, Knowledge management, and Rebeca
- Language:
- English
- Description:
- Modern organizations tend to constitute of communities of practice to cover the side effect of standardization and centralization of knowledge. The distributed nature of knowledge in groups, teams and other departments of organization and complexity of this tacit knowledge lead us to use community of practice as an environment to share knowledge. In this paper we propose an agent mediated community of a practice system using MAS-CommonKADS methodology. We support the principle of autonomy since every single agent, even those in the same community, needs its own autonomy in order to model an organization and its individuals correctly, using this approach, the natural model for an agent based on knowledge sharing system has been resulted. We presented all models of MAS-CommonKADS methodology required for developing the multi-agent system. We found MAS-CommonKADS useful to design Knowledge Management applications. Because of detailed description of agents, a resulted design model could be simply implemented. We modeled our system using Rebeca and verified it to show that by use of our system, knowledge sharing can be satisfied.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public
254. A multi-subpopulation bat optimization algorithm for economic dispatch problem with non-essential demand response
- Creator:
- Shen, Yanjun, Yang, Bo , Huang, Xiongfeng , Zhang, Yujiao , and Tan, Chao
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- economic dispatch, non-essential demand response, random wind power, bat algorithm, and multi-subpopulation
- Language:
- English
- Description:
- In this paper, we propose a new economic dispatch model with random wind power, demand response and carbon tax. The specific feature of the demand response model is that the consumer's electricity demand is divided into two parts: necessary part and non-essential part. The part of the consumer's participation in the demand response is the non-essential part of the electricity consumption. The optimal dispatch objective is to obtain the minimum total cost (fuel cost, random wind power cost and emission cost) and the maximum consumer's non-essential demand response benefit while satisfying some given constraints. In order to solve the optimal dispatch objective, a multi-subpopulation bat optimization algorithm (MSPBA) is proposed by using different search strategies. Finally, a case of an economic dispatch model is given to verify the feasibility and effectiveness of the established mathematical model and proposed algorithm. The economic dispatch model includes three thermal generators, two wind turbines and two consumers. The simulation results show that the proposed model can reduce the consumer's electricity demand, reduce fuel cost and reduce the impact on the environment while considering random wind energy, non-essential demand response and carbon tax. In addition, the superiority of the proposed algorithm is verified by comparing with the optimization results of CPLEX+YALMIP toolbox for MATLAB, BA, DBA and ILSSIWBA.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public
255. A multi-swarm synergetic optimizer for multi-knowledge extraction using rough set
- Creator:
- Yue, Benxian, Liu , Hongbo, Abraham , Ajith, and Badr, Youakim
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- Swarm intelligence, rough set, particle swarm optimization, and multi-knowledge extraction
- Language:
- English
- Description:
- Finding reducts is one of the key problems in the increasing applications of rough set theory, which is also one of the bottlenecks of the rough set methodology. The population-based reduction approaches are attractive to find multiple reducts in the decision systems, which could be applied to generate multi-knowledge and to improve decision accuracy. In this paper, we design a multi-swarm synergetic optimization algorithm (MSSO) for rough set reduction and multi-knowledge extraction. It is a multi-swarm based search approach, in which different individual trends to be encoded to different reduct. The approach discovers the best feature combinations in an efficient way to observe the change of positive region as the particles proceed throughout the search space. The performance of our approach is evaluated and compared with Standard Particle Swarm Optimization (SPSO) and Genetic Algorithms (GA). Empirical results illustrate that the approach can be applied for multiple reduct problems and multi-knowledge extraction effectively.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public
256. A multidimensional integration by parts formula for the Henstock-Kurzweil integral
- Creator:
- Lee, Tuo-Yeong
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- Henstock-Kurzweil integral, bounded variation in the sense of Hardy-Krause, and integration by parts
- Language:
- English
- Description:
- It is shown that if g is of bounded variation in the sense of Hardy-Krause on ∏m i=1 [ai , bi ], then gχ ∏m i=1 (ai ,bi ) is of bounded variation there. As a result, we obtain a simple proof of Kurzweil’s multidimensional integration by parts formula.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public
257. A multiple classification method based on the cloud model
- Creator:
- Lin , Lin and Ding, Gang
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- Cloud model, cloud transform, and multiple classification
- Language:
- English
- Description:
- Based on the randomness and fuzziness of the cloud model during the transformation from the qualitative concept to the quantitative numerical value, with the theory that any data distribution can be decompounded into several normal distributions, this paper puts forward a method of multi-classification based on the cloud model. By this method, multiple classification is transformed to a superposed cloud model with training samples as the cloud expectation, while the test samples are regarded as the `cloud droplets', and their classifications of membership degree in a cloud model can be calculated. Considering the effect of the number of training samples on the membership degree, the cloud model is weighted by the ratio of the total number of training samples to the number of training samples in a single class so that the data distribution of the samples can be balanced. The formula of multiple classification based on the cloud model has the structure identical to that of Support Vector Machines, and the hyper entropy in cloud models exerts similar punishment on the noise samples just like the loose coefficients in Support Vector Machines; therefore, the reasonability of the method is theoretically proved. Compared with Support Vector Machine, the method discussed in this paper does not require any large-scale quadratic programming, thus the algorithm of the method is simpler. Last but not the least, five types of data distribution samples are selected for the comparative experiment, and comparison is made with four other classification methods; the result shows that the accuracy and stability of the algorithm is high, and its implementations on the high dimensional multiple classifications are especially satisfactory.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public
258. A necessary and sufficient condition for the primality of Fermat numbers
- Creator:
- Křížek, Michal and Somer, Lawrence
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- Fermat numbers, primitive roots, primality, and Sophie Germain primes
- Language:
- English
- Description:
- We examine primitive roots modulo the Fermat number Fm = 2 2m + 1. We show that an odd integer n ≥ 3 is a Fermat prime if and only if the set of primitive roots modulo n is equal to the set of quadratic non-residues modulo n. This result is extended to primitive roots modulo twice a Fermat number.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public
259. A necessity measure optimization approach to linear programming problems with oblique fuzzy vectors
- Creator:
- Inuiguchi, Masahiro
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- fuzzy linear programming, oblique fuzzy vector, necessity vector, necessity measure, and Bender´s decomposition
- Language:
- English
- Description:
- In this paper, a necessity measure optimization model of linear programming problems with fuzzy oblique vectors is discussed. It is shown that the problems are reduced to linear fractional programming problems. Utilizing a special structure of the reduced problem, we propose a solution algorithm based on Bender's decomposition. A numerical example is given.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public
260. A Network Traffic Hybrid Prediction Model Optimized by Improved Harmony Search Algorithm
- Creator:
- Tian , Z., Li , S., Wang, Y., and Wang, X.
- Format:
- bez média and svazek
- Type:
- model:article and TEXT
- Subject:
- network traffic, grey model, Elman neural network, prediction, and improved harmony search
- Language:
- English
- Description:
- The telecommunication and Ethernet trafic prediction problem is studied. Network traffic prediction is an important problem of telecommunication and Ethernet congestion control and network management. In order to improve network traffic prediction accuracy, a network traffic hybrid prediction model was proposed by using the advantages of grey model and Elman neural network, grey model and Elman neural network predictive values were independently obtained, the different weight coefficients of two prediction models were given. In terms of weight coefficients optimization, an improved harmony search algorithm with better convergence speed and accuracy was proposed, the optimal weight coefficients of network traffic hybrid prediction model were determined through this algorithm, two prediction models results were multiplied by the weight coefficients to obtain the final prediction value. The network traffic sample data from an actual telecommunication network was collected as simulation object. The simulation results verified that the proposed network traffic hybrid prediction model based on improved harmony search algorithm has higher prediction accuracy.
- Rights:
- http://creativecommons.org/publicdomain/mark/1.0/ and policy:public