this paper aims to model system of ordinary differential equations by using a new hybrid gene expression programming algorithm. Gene expression programming is a recently developed evolutionary computation method for m...
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ISBN:
(纸本)9781479986460
this paper aims to model system of ordinary differential equations by using a new hybrid gene expression programming algorithm. Gene expression programming is a recently developed evolutionary computation method for model learning and knowledge discovery. the hybrid algorithm combined immune clonal selection algorithm and memetic algorithm with gene expression programming to find not only the structure of system of differential equations but also optimize its constant parameters. the idea of immune clone principle is incorporated into the evolution process to enhance the diversity of population and the memetic algorithm is introduced to improve the ability of local search. Experiments on benchmark problems have shown that the hybrid approach is able to provide highly competitive results compared withthat of conventional genetic programming applied to this problem.
A novel and simple combination of inductive logic programming with swarm intelligence is presented. the Ant-FOIL tightly integrates the well-known inductive logic programming rule-learner FOIL with Ant Colony System m...
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ISBN:
(纸本)9781479986460
A novel and simple combination of inductive logic programming with swarm intelligence is presented. the Ant-FOIL tightly integrates the well-known inductive logic programming rule-learner FOIL with Ant Colony System meta-heuristic. the hypotheses construction is guided by the ACS stochastic local decision policy depends on pheromone and heuristic information. Experiments in applying Ant-FOIL to well-known benchmarks shows that Ant-FOIL performs better than either its baseline algorithm (FOIL), and is at the same time competitive with more sophisticated approaches (kFOIL, nFOIL and Aleph).
Station-based bike sharing systems provide an inexpensive and flexible supplement to public transportation systems. However, due to spatial and temporal demand variation, stations tend to run full or empty over the co...
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Operational readiness and mission availability are two important standards in equipment supportability. To evaluate these two standards, an improved particle swarm optimization (PSO) algorithm to solve the mixed integ...
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ISBN:
(纸本)9781479986460
Operational readiness and mission availability are two important standards in equipment supportability. To evaluate these two standards, an improved particle swarm optimization (PSO) algorithm to solve the mixed integer programming (MIP) problems has been developed. the augmented Lagrange multiplier method is employed to deal withthe constraints, and special update strategy employed to restrict the swarm particles to lies only in integer positions. Tests on the two former mathematical models have verified the effectiveness of the proposed mixed technique, and it can be easily applied to other mixed integer programming with Constraint problem.
Text documents clustering is a popular unsupervised text mining tool. It is used for partitioning a collection of text documents into similar clusters based on the distance or similarity measure as decided by an objec...
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ISBN:
(纸本)9781467389150
Text documents clustering is a popular unsupervised text mining tool. It is used for partitioning a collection of text documents into similar clusters based on the distance or similarity measure as decided by an objective function. Text clustering algorithm often makes prior assumptions to satisfy objective function, which is optimized either through traditional techniques or meta-heuristic techniques. In text clustering techniques, the right decision for any document distribution is done using an objective function. Normally, clustering algorithms perform poorly when the configuration of the well-formulated objective function is not sound and complete. therefore, we proposed multi-objectives-based method namely, combine distance and similarity measure for improving the text clustering technique. Multi-objectives text clustering method is combined with two evaluating criteria which emerge as a robust alternative in several situations. In particular, the multi-objective function in the text clustering domain is not a popular, and it is a core issue that affects the performance of the text clustering technique. the performance of multi-objectives function is investigated using the k-mean text clustering technique. the experiments were conducted using seven standard text datasets. the results showed that the proposed multi-objectives based method outperforms the other measures in term of the performance of the text clustering, evaluated by using two common clustering measures, namely, Accuracy and F-measure.
the Belief-Desire-Intention (BDI) model is well suited for describing an agent's mental state. To model human reasoning with uncertainty and imprecision, fuzzy logic have been employed to represent beliefs for BDI...
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ISBN:
(纸本)9781479986460
the Belief-Desire-Intention (BDI) model is well suited for describing an agent's mental state. To model human reasoning with uncertainty and imprecision, fuzzy logic have been employed to represent beliefs for BDI agents in our previous work. In order that the BDI agents are more and more suitable for modelling our real world, a BDI agent programming language with fuzzied-belief based on a existing BDI agent programming language is developed in this paper. the new language is more flexible and human-like compared to non-fuzzy based BDI agent language in the real world applications. Particularly, it provides a more reasonable planning selection mechanism. the reasoning capability of the previous BDI language is improved due to the work in this paper.
Cloud computing providers in the infrastructure as a service (IaaS) layer provide their utility computing and IT services as virtual machines to customers, who then pay for resources based on time usage. One of the mo...
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ISBN:
(纸本)9781467395601
Cloud computing providers in the infrastructure as a service (IaaS) layer provide their utility computing and IT services as virtual machines to customers, who then pay for resources based on time usage. One of the most subtle challenges is pricing stagnant resources dynamically, which combines the static pricing strategy of active resources to maximize cloud computing profits. this paper investigates cloud dynamic pricing and proposes an efficient model that manages virtual machines in regards to revenue management, formulating the maximum expected reward under discrete finite horizon Markovian decisions, characterizing model properties under optimum controlling conditions, approximating optimal dynamic programming policy using a linear programming approach, developing a new algorithm based on this approximation, and finally presenting evaluation results. Our results provide fundamental insights into cloud computing revenue.
Central to many sentiment analysis tasks are sentiment lexicons (SLs). SLs exhibit polarity inconsistencies. Previous work studied the problem of checking the consistency of an SL for the case when the entries have ca...
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ISBN:
(纸本)9781941643723
Central to many sentiment analysis tasks are sentiment lexicons (SLs). SLs exhibit polarity inconsistencies. Previous work studied the problem of checking the consistency of an SL for the case when the entries have categorical labels (positive, negative or neutral) and showed that it is NP-hard. In this paper, we address the more general problem, in which polarity tags take the form of a continuous distribution in the interval [0, 1]. We show that this problem is polynomial. We develop a general framework for addressing the consistency problem using linear programming (LP) theory. LP tools allow us to uncover inconsistencies efficiently, paving the way to building SL debugging tools. We show that previous work corresponds to 0-1 integer programming, a particular case of LP. Our experimental studies show a strong correlation between polarity consistency in SLs and the accuracy of sentiment tagging in practice.
the VII All-Russian (withinternational participation) Scientific Technical conference 'Low-temperature plasma during the deposition of functional coatings' took place from 4-7 November 2015 at the Academy of ...
the VII All-Russian (withinternational participation) Scientific Technical conference 'Low-temperature plasma during the deposition of functional coatings' took place from 4-7 November 2015 at the Academy of Sciences of the Republic of Tatarstan and the Kazan Federal University. the conference was attended by over 150 people from Russia and abroad. the participants proposed a wide range of issues affecting the theoretical and experimental aspects of the problems of the physics of low-temperature plasma. We heard the reports of experts from leading universities and research organizations in the field of plasma physics: Moscow State University, St. Petersburg State University, MEPhI, Tomsk Polytechnic University, Institute of High Current Electronics SB RAS, etc. A series of works were devoted to the study of thin films obtained by low-temperature plasma. this year, work dedicated to the related field of heat mass transfer in multiphase media and low-temperature plasma was also presented. Of special interest were reports on the exploration of gas discharges with liquid electrolytic electrodes and the study of dusty plasmas. Kashapov Nail, ***., professor (Kazan Federal University)
this work discuss briefly the Elastic Flow Rerouting (EFR)-a traffic restoration strategy for protecting traffic flows in communication networks (including wireless networks). EFR aims at alleviating the trade-off bet...
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ISBN:
(纸本)9781479987849
this work discuss briefly the Elastic Flow Rerouting (EFR)-a traffic restoration strategy for protecting traffic flows in communication networks (including wireless networks). EFR aims at alleviating the trade-off between practicabilty of traffic restoration and the cost of network resources observed in existing networking solutions. We provide a discussion on the strategy and position it among the other strategies.
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