After years of development, the neural network classification, clustering and forecasting applications have a lot of development, but the neural network has the inevitable defects, if you enter the attribute set, the ...
详细信息
ISBN:
(纸本)9783037855744
After years of development, the neural network classification, clustering and forecasting applications have a lot of development, but the neural network has the inevitable defects, if you enter the attribute set, the classification boundaries are not clear, convergence low efficiency and accuracy, there may even be the state does not converge, using rough set theory, the right value to modify the function to be modified, and joined the contradictions sample test module, after the use of EEG to verify reached the deletion of number of features and the purpose to improve the classification accuracy.
Flowchart brings the advantage of efficiency into the program design. designers can achieve clearer structure refer to flowchart. It's a powerful method in the process of program design. However, the traditional f...
详细信息
ISBN:
(纸本)9781450353526
Flowchart brings the advantage of efficiency into the program design. designers can achieve clearer structure refer to flowchart. It's a powerful method in the process of program design. However, the traditional flowchart is only designed on single site. It leads to the low efficiency and less diversity. Based on these problems, this paper aims at using collaborative algorithm to complete the distributed flowchart design. The paper mainly solves the problems of the operation conflicts which come from different sites, and analyzes the typical consistency maintenance algorithm, constructs the flowchart model, analyzes the flowchart operations, devises the conflict resolution strategy and describes the consistency maintenance work flow. At last, a correctness proof is also given to validate the whole strategy.
Modern wireless communication applications are characterized by the need for advanced signal processing techniques such as Multiple-Input Multiple-Output (MIMO) technology for achieving high throughput and diversity a...
详细信息
The authors discuss the design of distributed and autonomous algorithms for producing social matching such as dancing pairs from groups of boys and girls, roommates for a boy dormitory, and job placement in the employ...
详细信息
algorithmic methods based on the theory of fixed-parameter tractability are combined with powerful computational platforms to launch systematic attacks on combinatorial problems of significance. As a case study, optim...
详细信息
algorithmic methods based on the theory of fixed-parameter tractability are combined with powerful computational platforms to launch systematic attacks on combinatorial problems of significance. As a case study, optimal solutions to very large instances of the NP-hard vertex cover problem are computed. To accomplish this, an efficient sequential algorithm and various forms of parallel algorithms are devised, implemented, and compared. The importance of maintaining a balanced decomposition of the search space is shown to be critical to achieving scalability. Target problems need only be amenable to reduction and decomposition. Applications in high throughput computational biology are also discussed.
This paper first presents a naive systolic algorithm for finding a closest point for each of n given points in linear time. Then, based on the algorithm, we propose linear-time systolic algorithms for the computation ...
详细信息
This paper first presents a naive systolic algorithm for finding a closest point for each of n given points in linear time. Then, based on the algorithm, we propose linear-time systolic algorithms for the computation of the visibility polygon and for the trapezoidal partition or triangulation of a polygonal region which may contain holes. The visibility problem among n vertical line segments in the plane is also solved.
With the rapid proliferation of RFID technologies, RFID has been introduced to the applications like safety inspection and warehouse management. Conventionally a number of deployment rules are specified for these appl...
详细信息
With the rapid proliferation of RFID technologies, RFID has been introduced to the applications like safety inspection and warehouse management. Conventionally a number of deployment rules are specified for these applications. This paper studies a practically important problem of rule checking over RFID tags, i.e., checking whether the specified rules are satisfied according to the RFID tags within the monitoring area. This rule checking function may need to be executed frequently over a large number of tags and therefore should be made efficient in terms of execution time. Aiming to achieve time efficiency, we respectively propose two protocols, CRCP and ECRCP. CRCP works based on collision detection, while ECRCP combines the collision detection and the logical features of the rules. Simulation results indicate that our protocols achieve much better performance than other solutions in terms of time efficiency.
This paper addresses the makespan minimization problem in scheduling flexible job shops whenever there exist separable sequence-dependent setup times. An extension to the neighborhood search functions of Mastrolilli a...
详细信息
This paper addresses the makespan minimization problem in scheduling flexible job shops whenever there exist separable sequence-dependent setup times. An extension to the neighborhood search functions of Mastrolilli and Gambradella, developed for the flexible job shop scheduling problem (FJSP), is provided. It is shown that under certain conditions such an extension is viable. Accordingly, a randomized neighborhood search function is introduced, and its best search parameters are determined experimentally using modified FJSP benchmark instances. A tabu search approach utilizing the proposed neighborhood search function is then developed, and experimentations are conducted using the modified instances to benchmark it against a lower bound. Experimental results show that on average, the tabu search approach is capable of achieving optimality gaps of below 10% for instances with low average setup time to processing time ratios. (C) 2015 Elsevier Inc. All rights reserved.
Mobile crowdsensing paradigms can be categorized into two classes: opportunistic sensing and participatory sensing, each of which has its advantage and disadvantage. The high flexibility of worker mobility in particip...
详细信息
Mobile crowdsensing paradigms can be categorized into two classes: opportunistic sensing and participatory sensing, each of which has its advantage and disadvantage. The high flexibility of worker mobility in participatory sensing leads to high task coverage but also high worker employment fee. The little human involvement in opportunistic sensing results in low worker employment fee but also low task coverage. In this paper, we propose a new mobile crowdsensing paradigm, named semi-opportunistic sensing, aiming to achieve both high task coverage and low worker employment fee. In this paradigm, each worker can provide multiple candidate moving paths for his/her trip, among which the service platform chooses one for the worker to undertake task(s). The platform selects workers and assigns tasks to them with an objective to optimize total task quality under the platform's incentive budget and workers' task performing time constraints. In this paper, we formulate the task allocation problem, prove its NP-hardness, and present two efficient heuristic algorithms. The first heuristic, named Best Path/Task first algorithm (BPT), always chooses the best path and task in a greedy manner. The second heuristic, named LP-Relaxation based algorithm (LPR), assigns paths and tasks with the largest values according to the LP-relaxation. We conduct extensive experiments on synthetic dataset and real-life traces. Experiment results show that the proposed semi-opportunistic sensing paradigm can significantly improve total task quality compared with opportunistic sensing. Moreover, the experiment results also validate the high efficiency of our proposed task allocation algorithms.
The two fundamental problems in machine learning (ML) are statistical analysis and algorithm design. The former tells us the principles of the mathematical models that we establish from the observation data. The latte...
详细信息
The two fundamental problems in machine learning (ML) are statistical analysis and algorithm design. The former tells us the principles of the mathematical models that we establish from the observation data. The latter defines the conditions on which implementation of data models and data sets rely. A newly discovered challenge to ML is the Rashomon effect, which means that data are possibly generated from a mixture of heterogeneous sources. A simple classification standard can shed light on emerging forms of ML. This article is part of a special issue on AI in China.
暂无评论