scholarly journals Dynamic Adjustment Strategy of China's Industrial Structure and Social Investment under the New Normal

2018 ◽  
Keyword(s):  
Industrial Structure ◽  
Social Investment ◽  
Dynamic Adjustment ◽  
New Normal ◽  
Adjustment Strategy

scholarly journals CHINA’S INDUSTRIAL STRUCTURE UPGRADE IN THE “NEW NORMAL”: EMPIRICAL TEST AND DETERMINANTS

2018 ◽  
Vol 63 (04) ◽  
pp. 1037-1058 ◽  
Author(s):  
WEN XIAO ◽  
JIA-DONG PAN ◽  
LI-YUN LIU
Keyword(s):  
Development Strategy ◽  
Industrial Structure ◽  
Empirical Test ◽  
Supply Side ◽  
New Normal ◽  
Dummy Variable ◽  
Technology Improvement ◽  
Policy Suggestions ◽  
Regional Economy Development ◽  
Supply Side Factors

This paper measures the index of industrial structure upgrade nationally, regionally and provincially by employing angle cosine method. The results show that China’s industrial structure has upgraded and the East is higher than the Northeast and the Midwest. The paper presents an empirical study to examine the effect of variables including demand-side factors, New Normal as a dummy variable and supply-side factors on industrial structure upgrading. It implies that New Normal is not significant, while consumption, investment, technology improvement and labor supply significantly facilitate the upgrade. It highlights policy suggestions designed to adopt innovation-driven strategy and regional economy development strategy.

scholarly journals A Dynamic Adjusting Novel Global Harmony Search for Continuous Optimization Problems

Symmetry ◽  
2018 ◽  
Vol 10 (8) ◽  
pp. 337 ◽  
Author(s):  
Chui-Yu Chiu ◽  
Po-Chou Shih ◽  
Xuechao Li
Keyword(s):  
Optimization Problems ◽  
Harmony Search ◽  
Continuous Optimization ◽  
Genetic Mutation ◽  
Dynamic Adjustment ◽  
Mutation Probability ◽  
Adjustment Strategy ◽  
Improved Harmony Search ◽  
Searching Ability ◽  
Continuous Optimization Problems

A novel global harmony search (NGHS) algorithm, as proposed in 2010, is an improved algorithm that combines the harmony search (HS), particle swarm optimization (PSO), and a genetic algorithm (GA). Moreover, the fixed parameter of mutation probability was used in the NGHS algorithm. However, appropriate parameters can enhance the searching ability of a metaheuristic algorithm, and their importance has been described in many studies. Inspired by the adjustment strategy of the improved harmony search (IHS) algorithm, a dynamic adjusting novel global harmony search (DANGHS) algorithm, which combines NGHS and dynamic adjustment strategies for genetic mutation probability, is introduced in this paper. Moreover, extensive computational experiments and comparisons are carried out for 14 benchmark continuous optimization problems. The results show that the proposed DANGHS algorithm has better performance in comparison with other HS algorithms in most problems. In addition, the proposed algorithm is more efficient than previous methods. Finally, different strategies are suitable for different situations. Among these strategies, the most interesting and exciting strategy is the periodic dynamic adjustment strategy. For a specific problem, the periodic dynamic adjustment strategy could have better performance in comparison with other decreasing or increasing strategies. These results inspire us to further investigate this kind of periodic dynamic adjustment strategy in future experiments.

scholarly journals Complexity Analysis of Pricing in a Multichannel Supply Chain with Spillovers from Online to Offline Sales

Complexity ◽  
2020 ◽  
Vol 2020 ◽  
pp. 1-17
Author(s):  
Fengxia Mai ◽  
Jianxiong Zhang ◽  
Rui Yang ◽  
Xiaojie Sun
Keyword(s):  
Supply Chain ◽  
Dynamic Pricing ◽  
Complexity Analysis ◽  
Spillover Effect ◽  
Dynamic Game ◽  
Period Doubling ◽  
Dynamic Adjustment ◽  
Adjustment Strategy ◽  
Adjustment Speed ◽  
The Stability

In recent years, many manufacturers have been selling their products to online consumers through e-tailers by adopting reselling mode and agency selling mode simultaneously. The sales from the online channels inevitably incur spillover effect to the traditional offline channels. This paper develops a dynamic pricing game model on the basis of a long-term gradient adjustment mechanism for a multichannel supply chain that consists of a manufacturer and an e-tailer and focuses on examining the impacts of spillover effect, agency fee, and adjustment speed on the stability and complexity of the dynamic game system. The results show that both a greater spillover effect and a higher agency fee can make the dynamic game system more stable, and a higher adjustment speed can destabilize the dynamic game system through period doubling bifurcation. Furthermore, it is interesting to find that the destabilization of the game system benefits the e-tailer and the supply chain while having little influence on the manufacturer, and thus the dynamic adjustment strategy may improve the supply chain efficiency.

scholarly journals Adaptive Bat Algorithm Optimization Strategy for Observation Matrix

2019 ◽  
Vol 9 (15) ◽  
pp. 3008 ◽  
Author(s):  
Zhihua Cui ◽  
Chunmei Zhang ◽  
Yaru Zhao ◽  
Zhentao Shi
Keyword(s):  
Bat Algorithm ◽  
Reconstruction Error ◽  
Optimization Strategy ◽  
Algorithm Optimization ◽  
Dynamic Adjustment ◽  
Memory Space ◽  
Adjustment Strategy ◽  
Reconstructed Signal ◽  
Observation Matrix ◽  
Signal Accuracy

Bat algorithm, as an optimization strategy of the observation matrix, has been widely used. Observation matrix has a direct impact on the reconstructed signal accuracy as a projection transformation matrix, and it has been widely used in various algorithms. However, for the traditional experimental process, randomly generated observation matrices often result in a larger reconstruction error and unstable reconstruction results. Therefore, it is a challenge to retain more feature information of the original signal and reduce reconstruction error. To obtain a more accurate reconstruction signal and less memory space, it is important to select an effective compression and reconstruction strategy. To solve this problem, an adaptive bat algorithm is proposed to optimize the observation matrix in this paper. For the adaptive bat algorithm, we design a dynamic adjustment strategy of the optimal radius to improve its global convergence ability. The results of our simulation experiments verify that, compared with other algorithms, it can effectively reduce the reconstruction error and has stronger robustness.

scholarly journals Updatable learned index with precise positions

2021 ◽  
Vol 14 (8) ◽  
pp. 1276-1288
Author(s):  
Jiacheng Wu ◽  
Yong Zhang ◽  
Shimin Chen ◽  
Jin Wang ◽  
Yu Chen ◽  
...  
Keyword(s):  
State Of The Art ◽  
Real Life ◽  
Index Structures ◽  
Dynamic Adjustment ◽  
New Paradigm ◽  
Adjustment Strategy ◽  
Tree Index ◽  
Synthetic Datasets ◽  
The Cost ◽  
New Framework

Index plays an essential role in modern database engines to accelerate the query processing. The new paradigm of "learned index" has significantly changed the way of designing index structures in DBMS. The key insight is that indexes could be regarded as learned models that predict the position of a lookup key in the dataset. While such studies show promising results in both lookup time and index size, they cannot efficiently support update operations. Although recent studies have proposed some preliminary approaches to support update, they are at the cost of scarifying the lookup performance as they suffer from the overheads brought by imprecise predictions in the leaf nodes. In this paper, we propose LIPP, a brand new framework of learned index to address such issues. Similar with state-of-the-art learned index structures, LIPP is able to support all kinds of index operations, namely lookup query, range query, insert, delete, update and bulkload. Meanwhile, we overcome the limitations of previous studies by properly extending the tree structure when dealing with update operations so as to eliminate the deviation of location predicted by the models in the leaf nodes. Moreover, we further propose a dynamic adjustment strategy to ensure that the height of the tree index is tightly bounded and provide comprehensive theoretical analysis to illustrate it. We conduct an extensive set of experiments on several real-life and synthetic datasets. The results demonstrate that our method consistently outperforms state-of-the-art solutions, achieving by up to 4X for a broader class of workloads with different index operations.

China’s economy: Dipping into “New Normal”

2015 ◽  
pp. 134-158 ◽  
Author(s):  
P. Mozias
Keyword(s):  
Economic Growth ◽  
Industrial Structure ◽  
Economic Resources ◽  
Development Economic ◽  
Shadow Banking ◽  
Institutional Reforms ◽  
Macroeconomic Factors ◽  
New Normal ◽  
Investment Demand ◽  
Good Potential

The article deals with the peculiarities of the current stage of China’s economic development. Economic growth has slowed down in recent years because of weakening of all its drivers, e.g. domestic consumption and investment demand as well as exports. China’s entry into ‘new normal’ is caused both by structural and macroeconomic factors. The former include an exhaustion of labor surplus in traditional agriculture, waning of “demographic dividend”, rebalancing towards services in industrial structure, and diminishing returns of economic resources used. But all of these are aggravated with the chronic overcapacity and huge debts of the corporate and public sectors, not least because of the expanding shadow banking. Economic growth cannot be reaccelerated with a new flooding of cheap finance, and responding to new challenges the authorities have put forward a new program of institutional reforms in 2013-2014. Risks of а hard landing do exist, but, by and large, China is equipped with a good potential to cope with the negative trends and sustain a course of steady development.

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