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141.
This paper describes a new multiobjective interactive memetic algorithm applied to dynamic location problems. The memetic
algorithm integrates genetic procedures and local search. It is able to solve capacitated and uncapacitated multi-objective
single or multi-level dynamic location problems. These problems are characterized by explicitly considering the possibility
of a facility being open, closed and reopen more than once during the planning horizon. It is possible to distinguish the
opening and reopening periods, assigning them different coefficient values in the objective functions. The algorithm is part
of an interactive procedure that asks the decision maker to define interesting search areas by establishing limits to the
objective function values or by indicating reference points. The procedure will be applied to some illustrative location problems. 相似文献
142.
John A. Ford Yasushi Narushima Hiroshi Yabe 《Computational Optimization and Applications》2008,40(2):191-216
Conjugate gradient methods are appealing for large scale nonlinear optimization problems, because they avoid the storage of
matrices. Recently, seeking fast convergence of these methods, Dai and Liao (Appl. Math. Optim. 43:87–101, 2001) proposed a conjugate gradient method based on the secant condition of quasi-Newton methods, and later Yabe and Takano (Comput.
Optim. Appl. 28:203–225, 2004) proposed another conjugate gradient method based on the modified secant condition. In this paper, we make use of a multi-step
secant condition given by Ford and Moghrabi (Optim. Methods Softw. 2:357–370, 1993; J. Comput. Appl. Math. 50:305–323, 1994) and propose two new conjugate gradient methods based on this condition. The methods are shown to be globally convergent
under certain assumptions. Numerical results are reported. 相似文献
143.
This paper presents an interactive method for solving general 0-1 multiobjective linear programs using Simulated Annealing and Tabu Search. The interactive protocol with the decision maker is based on the specification of reservation levels for the objective function values. These reservation levels narrow the scope of the search in each interaction in order to identify regions of major interest to the decision maker. Metaheuristic approaches are used to generate potentially nondominated solutions in the computational phases. Generic versions of Simulated Annealing and Tabu Search for 0-1 single objective linear problems were developed which include a general routine for repairing unfeasible solutions. This routine improves significantly the results of single objective problems and, consequently, the quality of the potentially nondominated solutions generated for the multiobjective problems. Computational results and examples are presented. 相似文献
144.
An active set subspace Barzilai-Borwein gradient algorithm for large-scale bound constrained optimization is proposed. The
active sets are estimated by an identification technique. The search direction consists of two parts: some of the components
are simply defined; the other components are determined by the Barzilai-Borwein gradient method. In this work, a nonmonotone
line search strategy that guarantees global convergence is used. Preliminary numerical results show that the proposed method
is promising, and competitive with the well-known method SPG on a subset of bound constrained problems from CUTEr collection.
This work was supported by the 973 project granted 2004CB719402 and the NSF project of China granted 10471036. 相似文献
145.
Philippe Galinier 《Discrete Applied Mathematics》2008,156(2):267-279
Let G=(V,E) be a graph with vertex set V and edge set E. The k-coloring problem is to assign a color (a number chosen in {1,…,k}) to each vertex of G so that no edge has both endpoints with the same color. The adaptive memory algorithm is a hybrid evolutionary heuristic that uses a central memory. At each iteration, the information contained in the central memory is used for producing an offspring solution which is then possibly improved using a local search algorithm. The so obtained solution is finally used to update the central memory. We describe in this paper an adaptive memory algorithm for the k-coloring problem. Computational experiments give evidence that this new algorithm is competitive with, and simpler and more flexible than, the best known graph coloring algorithms. 相似文献
146.
The Maximum Clique Problem (MCP) is regarded here as the maximization of an indefinite quadratic form over the canonical simplex. For solving MCP an algorithm based upon Global Optimality Conditions (GOC) is applied. Furthermore, each step of the algorithm is analytically investigated and tested. The computational results for the proposed algorithm are compared with other Global Search approaches. 相似文献
147.
High Efficiency Video Coding (HEVC) is a new video coding standard achieving about a 50% bit rate reduction compared to the popular H.264/AVC High Profile with the same subjective reproduced video quality. Better coding efficiency is attained, however, at the cost of significantly increased encoding complexity. Therefore, fast encoding algorithms with little loss in coding efficiency is necessary for HEVC to be successfully adopted for real applications. In this paper we propose a fast encoding technique applicable to HEVC all intra encoding. The proposed fast encoding technique consists of coding unit (CU) search depth prediction, early CU splitting termination, and fast mode decision. In CU search depth prediction, the depth of encoded CU in the current coding tree unit (CTU) is limited to predicted range, which is mostly narrower than the full depth range. Early CU splitting skips mode search of its sub-CUs when rate distortion (RD) cost of current CU is below the estimated RD cost at the current CU depth. RD cost and encoded CU depth distribution of the collocated CTU of the previous frame are utilized both to predict the encoding CU depth search range and to estimate the RD cost for CU splitting termination. Fast mode decision reduces the number of candidate modes for full rate distortion optimized quantization on the basis of the low complexity costs computed in the preceding rough mode decision step. When all these three methods are applied, proposed fast HEVC intra encoding technique reduces the encoding time of the reference encoder by 57% on the average, with only 0.6% of coding efficiency loss in terms of Bjontegaard delta (BD) rate increase under the HEVC common test conditions. 相似文献
148.
Anupindi and Bassok investigate the impact of centralizing the stocks in a one-manufacturer-two-retailer supply chain with consumer search. They observed through numerical studies that in the decentralized scenario, the retailers’ order quantities are monotonic in the consumer search probability. This paper provides an analytical justification of this monotonicity. 相似文献
149.
B. S. Goh 《Journal of Optimization Theory and Applications》2009,142(2):275-289
We show that, for an unconstrained optimization problem, the long-term optimal trajectory consists of a sequence of greatest
descent directions and a Newton method in the final iteration. The greatest descent direction can be computed approximately
by using a Levenberg-Marquardt like formula. This implies the view that the Newton method approximates a Levenberg-Marquardt
like formula at a finite distance from the minimum point, instead of the standard view that the Levenberg-Marquadt formula
is a way to approximate the Newton method. With the insight gained from this analysis, we develop a two-dimensional version
of a Levenberg-Marquardt like formula. We make use of the two numerically largest components of the gradient vector to define
here new search directions. In this way, we avoid the need of inverting a high-dimensional matrix. This reduces also the storage
requirements for the full Hessian matrix in problems with a large number of variables.
The author thanks Mark Wu, Professors Sanyang Liu, Junmin Li, Shuisheng Zhou and Feng Ye for support and help in this research
as well as the referees for helpful comments. 相似文献
150.
POPMUSIC for the point feature label placement problem 总被引:1,自引:0,他引:1
Point feature label placement is the problem of placing text labels adjacent to point features on a map so as to maximize legibility. The goal is to choose positions for the labels that do not give rise to label overlaps and that minimize obscuration of features. A practical goal is to minimize the number of overlaps while considering cartographic preferences. This article proposes a new heuristic for solving the point feature label placement problem based on the application of the POPMUSIC frame. Computational experiments show that the proposed heuristic outperformed other recent metaheuristics approaches in the literature. Experiments with problem instances involving up to 10 million points show that the computational time of the proposed heuristic increases almost linearly with the problem size. New problem instances based on real data with more than 13,000 labels are proposed. 相似文献