Lei Wang

Tongji University, Shanghai, Shanghai Shi, China

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Publications (153)255.41 Total impact

  • Weian Guo · Lei Wang · Qidi Wu
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    ABSTRACT: In current years, Biogeography-Based Optimization (BBO), a novel Evolutionary Algorithm (EA), has drawn a lot of attention due to its dramatic performance. In our previous work, BBO's migration models for single-objective problem (SOP) have been investigated to reveal their effects to algorithm's performance. However to date, there is a few investigation about migration models for Multi-Objective Problems (MOPs) which are common in practice though more difficult. To make BBO competitive in dealing with MOPs, migration models of BBO are explored and exploited in this paper. One contribution of our work is that we propose Multi-objective BBO (MOBBO). By comparing MOBBO with other popular MOEAs, this algorithm is competent to handle MOPs. Besides, we present and compare six principal migration models. In comparisons, we find that Trapezoidal Migration Model performs well for MOPs, while its performance is inferior to other migration models for SOPs. Besides, Quadratic Migration Model's performance for MOPs is worse, while it has a good performance to solve SOPs. These demonstrate that the conclusion to evaluate migration models for SOPs does not hold for MOPs, so another contribution in this paper is that we reevaluate migration models for MOPs in an empirical way, which is helpful to design migration models for MOBBO.
    No preview · Article · Jan 2016 · Information Sciences
  • Weian Guo · Ming Chen · Lei Wang · Yanfen Mao · Qidi Wu
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    ABSTRACT: Optimization is a classical issue and in many areas that are bound up with people’s daily life. In current decades, with the development of human civilization and industry society, many complicated optimization problems are raised. In the meantime, corresponding novel approaches are constantly proposed for solving these problems. One of them is meta-heuristics, which is inspired from natural phenomena and contains many kinds of algorithms. The classical meta-heuristic algorithms have exhibited their superiority in dealing optimization problems, especially for specific problems such as combinatorial optimization. As a novel meta-heuristic algorithm, biogeography-based optimization (BBO), inspired from the science of biogeography, has its own characteristics and exhibits a huge potential in computation and optimization. According to current investigations and analysis on this algorithm, it has not only achieved a great success in numerical optimization problems, but also been implemented in various kinds of applications, and drawn worldwide attentions. In this paper, we present a survey for this algorithm. First, we introduce the basic operators of BBO, including migration and mutation. For migration operator, it mimics species migration among islands, which provides a recombination way for candidate solutions to interact with each other so that the whole population can be improved. Besides linear migration model, several other popular migration models are also introduced and the corresponding performances are analyzed. For mutation operator, the design of BBO is different from other meta-heuristics. In standard BBO, different candidate solutions have different migration rates and the rate assignment is influential to BBO’s performance. Second, we summarized some popular variants of BBO and related hybrid algorithms that significantly enhance BBO’s performance. This part introduces the development of this algorithm and helps readers understand the way to choose a suitable version of BBO for a given problem. The way to improve algorithms’ performances helps readers design new variants of BBO for specific problems. Third, we present the evaluation of BBO’s performance for both numerical and practical problems. The results demonstrate BBO is competent to solve optimization problems. Despite so many achievements of BBO, some open issues that should be considered and solved in future work in order to make this algorithm more competitive in meta-heuristics.
    No preview · Article · Jan 2016 · Neural Computing and Applications
  • Yantai Huang · Hongjun Tian · Lei Wang
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    ABSTRACT: The optimization of energy consumption, with consequent cost reduction, is one of the main challenges for the present and future smart grid. Demand response (DR) program is expected to be vital in home energy management system (HEMS) which aims to schedule the operation of appliances to save energy costs by considering customer convenience as well as characteristics of electric appliances. The DR program is a challenging optimization problem especially when the formulations are non-convex or NP-hard problems. In order to solve this challenging optimization problem efficiently, an effective heuristic approach is proposed to achieve a near optimal solution with low computational costs. Different from previously proposed methods in literatures which are not suitable to be run in embedded devices such as a smart meter. The proposed algorithm can be implemented in an embedded device which has severe limitations on memory size and computational power, and can get an optimal value in real-time. Numerical studies were carried out with the data simulating practical scenarios are provided to demonstrate the effectiveness of the proposed method.
    No preview · Article · Dec 2015 · International Journal of Electrical Power & Energy Systems
  • Weian Guo · Ming Chen · Lei Wang · Qidi Wu
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    ABSTRACT: As a novel Evolutionary Algorithm (EA), Biogeography-Based Optimization (BBO), inspired by the science of biogeography, draws much attention due to its significant performance in both numerical simulations and practical applications. In BBO, the features in poor solutions have a large probability to be replaced by the features in good solutions. The replacement operator is termed migration. However, the replacement causes a loss of the features in poor solutions, breaks the diversity of population and may lead to a local optimal solution. To overcome this, we design a novel migration operator to propose Backtracking BBO (BBBO). In BBBO, besides the regular population, an external population is employed to record historical individuals. The size of external population is the same as the size of regular population. The external population and regular population are used together to generate the next population. After that, the individuals in external population are randomly selected to be updated by the individuals in current population. In this way, the external population in BBBO can be considered as a memory to take part in the evolutionary process. The memory takes into account both current and historical data to generate next population, which enhances algorithm’s ability in exploring searching space. In numerical simulation, 14 classical benchmarks are employed to test BBBO’s performance and several classical nature inspired algorithms are use in comparison. The results show that the strategy in BBBO is feasible and very effective to enhance algorithm’s performance. In addition, we apply BBBO to mechanical design problems which involve constraints in optimization. The comparison results also exhibit that BBBO is very competitive in solving practical optimization problems.
    No preview · Article · Dec 2015 · Applied Intelligence
  • Yiu Fai Tsang · Lei Wang · Hong Chua
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    ABSTRACT: A coal slag-packed biotrickling filter inoculated with autotrophic sulphide oxidizing and ammonia oxidizing bacteria was successfully operated for co-treating hydrogen sulphide (H2S) and ammonia (NH3). Excellent removal efficiencies of H2S (98.5%) and NH3 (99.9%) were obtained at loadings of up to 120g H2Sm-3h-1 and 80g NH3m-3h-1, respectively. The inhibitory effects of selected pollutants and metabolic products on the treatment performance were evaluated through mass balance and bacterial community analyses. The presence of NH3 significantly affected the composition of metabolic products of sulphide oxidation. Elemental sulphur was the dominant metabolite that ranged from 35% to 65%, whereas the amount of sulphite and thiosulphate generally increased up to 20%. However, a similar trend in the distribution of by-products to the results of nitrogen mass balance from sole NH3 removal was observed. The predominant bacteria were also changed with different loading ratios (H2S:NH3).
    No preview · Article · Dec 2015
  • Weian Guo · Yan Zhang · Ming Chen · Lei Wang · Qidi Wu
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    ABSTRACT: In current decades, various Evolutionary Algorithms(EAs) raise as well as many kinds of benchmarks are popular in evaluations of EAs' performances. Since there exists randomness in EAs' performances, the evaluations are made by a large number of runs in simulations or experiments in order to present a relatively fair comparison. However, there still exit several problems that have not been well explained. Does it make sense to deem two algorithms have equal ability if they have same final results? Is it convinced to decide winners or losers in comparisons just by tiny difference in performances? Besides the final results, how to compare algorithms' performances during the optimization iterations? In this paper, a neural network classifier based on extreme learning machine (ELM) is proposed to solve these problems. A novel role of classifier is first proposed to convince the differences between algorithms. If the classifier succeeds to classify algorithms based on their performances recorded in all generations, we deem the two algorithms have so convinced difference that comparisons of two algorithms can reflect algorithms' disparity. Therefore, the conclusions to judge the two algorithms are feasible and acceptable. Otherwise, if classifiers cannot distinguish two algorithms, we deem the two have similar performances so that it is meaningless to differ two algorithms just by tiny differences. By employing a set of classical benchmarks and six EAs, the simulations and computations are conducted. According to the analysis results, the proposed classifier can provide more information to reflect true abilities of algorithms, which is a novel view to compare EAs.
    No preview · Article · Nov 2015 · Neurocomputing
  • Qiang Sheng · Lei Wang · Jihua Wu
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    ABSTRACT: Wetland creation or restoration in degraded areas has become a new type of disturbance worldwide. Coastal wetlands serve a vital role in global carbon cycles; thus, it is important to understand the impacts of wetland creation on carbon storage functions. Carbon emissions and accumulation in wetlands are reported to be highly site-specific depending on factors such as salinity, plant type and productivity, and water table. This study investigated the effects of different salinities (<2‰, ~5‰ and >10‰) on greenhouse gas emissions and carbon sequestration of created wetlands in the Yangtze River estuary. CH4 emissions significantly declined with increasing salinity, likely because of the higher sediment sulfate content at higher salinities. CO2 emissions were highest at intermediate salinities (~5‰). In unvegetated sites, the absolute CO2 emission equivalent was 0.178kgm-2y-1 in the <2‰ salinity treatment, which was 8.09 times higher than the >10‰ salinity treatment. In vegetated sites, the <2‰ salinity treatment had the highest annual net flux of carbon. Thus, despite the high carbon emission of low salinity wetland, enhanced plant productivity resulted in a high carbon absorption rate. Overall, these results demonstrate that the presence of vegetation altered the effects of salinity on carbon equivalency in created wetlands. This study suggests that to conserve the wetland carbon sink function, landscape design for wetland restoration in estuarine regions should consider creating open water wetland in high salinity regions and restoring vegetation in low salinity regions to facilitate the growth of macrophytes such as Phragmites australis.
    No preview · Article · Nov 2015
  • Source
    He Chen · Jinfeng Niu · Tao Qin · Qi Ma · Lei Wang · Guowei Shu
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    ABSTRACT: Background. Lactobacillus acidophilus not only improves the intestinal flora balance but also inhabits the growth of undesirable microorganisms in intestine, which is benefit to the health of humans and animals. Plackett-Burman and steepest ascent experiment are the rapid and concise ways of screening the main effective factors. This study is aimed to select the main influence factors and optimize the medium for Lactobacillus acidophilus by Plackett-Burman experiment and steepest ascent experiment. Material and methods. The ideal carbon source was screened among glucose, maltose, lactose and whey powder, and the ideal nitrogen source was screened among casein hydrolysate, peptone, yeast extract powder, fish meal, carbamide, ammonium sulfate and sodium nitrate by single factor experiment. Plackett-Burman and steepest ascent experiment were applied to screen the main effective factors of Lactobacillus acidophilus among peptone, beef extract, yeast extract powder, glucose, K2HPO4, C6H14O7N2, CH3COONa, MgSO4 and Tween-80. Result. The results indicated that glucose (p = 0.01510) as negative factor and K2HPO4 (p = 0.02017) as positive effect were the significant growth factors of Lactobacillus acidophilus, CH3COONa (p = 0.09273) as positive effect was an important factor, and the optimized medium was as follows: glucose - 21 g/L, K2HPO4 - 3.5 g/L, CH3COONa - 6.5 g/L, peptone - 10 g/L, beef extract - 8 g/L, yeast extract powder - 8 g/L, C6H14O7N2 - 2 g/L, MgSO4 - 0.2 g/L and Tween-80 - 1 mL/L when the maximum viable count could achieve 2.72·109 cfu/mL. Discussion. The experimental model is reliable and the experimental results are of good stability. Variance analysis is performed to determine the adequacy and significance of the linear model. Thus, Plackett-Burman and steepest ascent experiment improve the veracity of optimization the medium for Lactobacillus acidophilus compared with the previous research.
    Preview · Article · Sep 2015 · Acta Scientiarum Polonorum, Technologia Alimentaria
  • Source
    Yiu Fai Tsang · Lei Wang · Hong Chua
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    ABSTRACT: A biotrickling filter packed with coal slag as packing medium was continuously used for more than 9 months under high ammonia loading rates of up to 140 g/m3/h. Nitrogen mass balance and microbial community analysis were conducted to evaluate the inhibitory effects of high ammonia concentration and metabolic by-products on the rates of nitrification. Ammonia removal efficiency reached above 99% at an empty bed retention time of as low as 8 s wheninlet concentrations were below 350 ppm. The maximum and critical elimination capacitiesof the biotrickling filter were 118 g/m3/h and 108.1 g/m3/h, respectively. Kinetics analysisresults showed that less than 2.5 s was required for the biotrickling filter with pH controlto treat ammonia at concentrations of up to 500 ppm in compliance with the Taiwan EPAstandard (outlet NH3< 1 ppm). Results of mass balance and microbial community analysis indicated that complete removal was mainly contributed by the activities of autotrophic ammonia oxidizing bacteria and not by physical absorption or adsorption at low loading rates. However, at high inlet loadings, ammonium became the dominant by-product due to inhibitory effects of high ammonia concentration on the bacterial community.
    Full-text · Article · Sep 2015 · Process Safety and Environmental Protection
  • Source
    Yiu Fai Tsang · Lei Wang · Hong Chua

    Full-text · Article · Aug 2015 · The Chemical Engineering Journal
  • Wuzhao Li · Lei Wang · Xingjuan Cai · Junjie Hu · Weian Guo
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    ABSTRACT: In classic evolutionary algorithms (EAs), solutions communicate each other in a very simple way so the recombination operator design is simple, which is easy in algorithms’ implementation. However, it is not in accord with nature world. In nature, the species have various kinds of relationships and affect each other in many ways. The relationships include competition, predation, parasitism, mutualism and pythogenesis. In this paper, we consider the five relationships between solutions to propose a co-evolutionary algorithm termed species co-evolutionary algorithm (SCEA). In SCEA, five operators are designed to recombine individuals in population. A set including several classical benchmarks are used to test the proposed algorithm. We also employ several other classical EAs in comparisons. The comparison results show that SCEA exhibits an excellent performance to show a huge potential of SCEA in optimization.
    No preview · Article · Jun 2015 · Neural Computing and Applications
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    ABSTRACT: Undisturbed natural wetlands are important carbon sinks due to their low soil respiration. When compared with inland alpine wetlands, estuarine wetlands in densely populated areas are subjected to great pressure associated with environmental pollution. However, the effects of water pollution and eutrophication on soil respiration of estuarine and their mechanism have still not been thoroughly investigated. In this study, two representative zones of a tidal wetland located in the upstream and downstream were investigated to determine the effects of water organic pollution and eutrophication on soil respiration of estuarine wetlands and its mechanism. The results showed that eutrophication, which is a result of there being an excess of nutrients including nitrogen and phosphorus, and organic pollutants in the water near Shang shoal located upstream were higher than in downstream Xia shoal. Due to the absorption and interception function of shoals, there to be more nitrogen, phosphorus and organic matter in Shang shoal soil than in Xia shoal. Abundant nitrogen, phosphorus and organic carbon input to soil of Shang shoal promoted reproduction and growth of some highly heterotrophic metabolic microorganisms such as β-Proteobacteria, γ-Proteobacteria and Acidobacteria which is not conducive to carbon sequestration. These results imply that the performance of pollutant interception and purification function of estuarine wetlands may weaken their carbon sequestration function to some extent.
    Preview · Article · May 2015 · PLoS ONE
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    ABSTRACT: Five autotrophic strains isolated from non-photosynthetic microbial communities (NPMCs), which were screened from oceans with high CO2 fixing capability, were identified as Ochrobactrum sp. WH-2, Stenotrophomonas sp. WH-11, Ochrobactrum sp. WH-13, Castellaniella sp. WH-14, and Sinomicrobium oceani WH-15. The CO2 fixation pathways of all these strains were Calvin-Benson-Bassham pathway. These strains could metabolize multifarious organic compounds, which allowed switching them to autotrophic culture after enrichment in heterotrophic culture. The central composite response surface method indicated that these strains possessed many interactive effects, which increased the CO2 fixing efficiency of a combined community composed of these strains by 56 %, when compared with that of the single strain. Furthermore, another combined community composed of these autotrophic strains and NPMC had richer interactive relationships, with CO2 fixing efficiency being 894 % higher than that of the single strain and 148 % higher than the theoretical sum of the CO2 fixing efficiency of each of its microbial components. The interaction between strictly heterotrophic bacteria in NPMC and isolated autotrophic strains played a crucial role in improving the CO2 fixing efficiency, which not only eliminated self-restraint of organic compounds generated during the growth of autotrophic bacteria but also promoted its autotrophic pathway.
    Full-text · Article · May 2015 · Applied biochemistry and biotechnology
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    ABSTRACT: The seawater samples collected from many different areas with different depth in the South China Sea were cultivated using different electron donors respectively. And the variation in the potential carbon fixation capability ( PCFC ) of non-photosynthetic microbial community (NPMC) in seawater with different depth was determined after a cycle of cultivation through the statistic analysis. In addition, the cause for the variation was clarified through analyzing key gene abundance regarding CO2 fixation and characteristics of seawater with different depth. The result showed that the PCFCs of NPMC in seawater with different depth were generally low and had no significant difference when using NaNO2 as the electron donor. The PCFC of NPMC in surface seawater was higher than that in deep seawater when using H2 as the electron donor, on the contrary, the PCFC of NPMC in deep seawater was higher than that in surface seawater when using Na2S2O3 as the electron donor. The abundance of the main CO2 fixation gene cbbL in surface seawater was higher than that in deep seawater while the cbbM gene abundance in deep seawater was higher than that in surface seawater. Most hydrogen-oxidizing bacteria had the cbbL gene, and most sulfur bacteria had the cbbM gene. The tendency of seawater cbbL/cbbM gene abundance with the change of depth revealed that there were different kinds of bacteria accounting for the majority in NPMC fixing CO2 at different depth of ocean, which led to different response of PCFC of NPMC at different depth of the sea to different electron donors. The distributions of dissolved oxygen and inorganic carbon concentration with the change of the depth of the sea might be an important reason leading to the difference of NPMC structure and even the difference of PCFC at different depth of the sea.
    No preview · Article · May 2015 · Huan jing ke xue= Huanjing kexue / [bian ji, Zhongguo ke xue yuan huan jing ke xue wei yuan hui "Huan jing ke xue" bian ji wei yuan hui.]
  • Tao Qin · Lei Wang · Dan Zhao · Min Zhu
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    ABSTRACT: Peer-to-Peer system has achieved great success with millions of end users in the past several years. P2P traffic has occupied about 60-80 % of the total traffic volumes, which greatly consumes network bandwidth and causes congestions. To achieve the goal of efficacious P2P system management in the monitored network, in this paper we develop a framework named CUFTI (Core Users Finding and Traffic Identification). The core users are referred as long-lived peers, and we focus on life-time characteristics of coexisting peers within each snapshot of the overlay. Based on the analysis results of user’s behaviour in PPlive system, we develop an accurate model to forecast the peer’s residual life-time and identify the long-lived peers. Furthermore, we develop a flow identification model for P2P traffic management of those core users. Based on the analysis results of actual traffic traces, we find the P2P traffic flows are composed of data and control packets. Most of the control packets appear at the beginning and end of each flow to establish and close the communication between peers. We employ the direction and payload length of the control packets at the beginning of the flow as features to perform flow identification. Experimental results based on traces collected from the Northwest Region Center of CERNET (China Education and Research Network) show that the newly developed methods outperforms other existing methods with lower false negative rate (FNR) and false positive rate (FPR).
    No preview · Article · Apr 2015 · Peer-to-Peer Networking and Applications
  • Tao Qin · Lei Wang · Zhaoli Liu · Xiaohong Guan
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    ABSTRACT: Application identification plays an essential role in network management such as intrusion detection and security monitoring. But the continuous growth of bandwidth and massive amount of packets pose serious challenges for efficacious and accurate application identification. In this paper, we develop a new method to reduce the number of packets being processed while achieving the goal of accurate P2P and VoIP application identification. Firstly, we employ the Bi-flow model to aggregate traffic packets into Bi-flow, which can capture the exchange behavior characteristics between different terminals. Then we employ the signature of Packet Size Distribution (PSD) to capture flow dynamics, which is defined as the payload length distribution probability of the packets in one Bi-flow. Secondly, we collect PSD of several different P2P and VoIP applications and the analysis results show that PSD of different applications are different with each other, which can be used as features to perform traffic identification. We also find the PSD characteristics of one Bi-flow can be captured by its first few packets, which demonstrate our methods can identify the Bi-flow quickly after its establishment. We employ the Renyi cross entropy to perform identification by calculating the similarity between PSD of the Bi-flow being identified and that of specific application. If the similarity is higher than a selected threshold, the Bi-flow being identified is classified to the specific application. Finally, as the PSD is a type of probability feature which is not sensitive to packet lose, we integrate the Poisson sampling method into our framework to process the massive data in backbone networks. Experimental results using the artificial and actual traces collected from monitoring platform in the Northwest Center of CERNET (China Education and Research Network) verify the accuracy and robustness of our method.
    No preview · Article · Mar 2015 · Knowledge-Based Systems
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    ABSTRACT: The Vicat softening temperature, melt and crystallization behavior, as well as the mechanical properties of polylactic acid (PLA)/nucleating agent (TMC-328) composites with different TMC contents were investigated. PLA/TMC composites had a modulus–temperature curve characteristic of polymers in three phases, and these phases shifted with increasing TMC concentration. Non-isothermal differential scanning calorimetry was applied to investigate the heat resistance mechanism of PLA. The heat resistant temperature was positively correlated with the degree of crystallinity, crystallization rate constant, and cold crystallization rate constant. Moreover, the arrangement and movement of molecular chains influenced the heat resistance of PLA, with an increased rigid amorphous fraction improving the heat resistance between the glass transition and cold crystallization temperatures. In conclusion, addition of the nucleating agent enhanced the crystallizability of PLA, thereby improving the heat resistance of PLA. With 0.2% (wt/wt) TMC, the Vicat softening temperature reached 134 °C, about 2.1 times that of the neat PLA (64.7 °C). An increase in the dose of nucleating agent had little impact on the tensile strength of PLA/TMC composites, but the tensile elastic modulus was increased with a higher dose of nucleating agent, after an initial decrease.KeywordsPolylactic acidNucleating agentHeterogeneous nucleationCrystallizationHeat resistance
    No preview · Article · Feb 2015 · Materials and Design
  • Xingjuan Cai · Wuzhao Li · Qi Kang · Lei Wang · Qidi Wu
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    ABSTRACT: RNA secondary structure is one important problem in bioinformatics. In this paper, one discrete binary adaptive bat algorithm is designed to solve it. In the standard version, pulse rate is exponential increased significantly, and then, pulse rate keeps a constant in most generations, this may result a fix selection pressure. To provide a large selection pressure, a linearly dynamic pulse rate selection strategy is designed. Furthermore, due to the special requirements of RNA secondary structure problem, Sigmoid function is also employed to determine the binary-value of each feature. Ten sequences from the comparative RNA website were selected for the evaluation of the proposed method. Simulation results show adaptive bat algorithm is better than Mfold.
    No preview · Article · Feb 2015 · Journal of Computational and Theoretical Nanoscience
  • Xingjuan Cai · Wuzhao Li · Qi Kang · Lei Wang · Qidi Wu

    No preview · Article · Jan 2015 · International Journal of Innovative Computing and Applications
  • Xingjuan Cai · Lei Wang · Qi Kang · Qidi Wu
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    ABSTRACT: Bat algorithm is a novel swarm intelligent algorithm inspired by the echolocation behaviour of bats. Pulse rate of emission is one important parameter, which is adjusted in an exponential manner in the standard version, however, this manner provides a fast convergent behaviour in the first several generations. With this manner, the exploitation capability is limited. In this paper, a new linear adjusted manner is employed to enhance the local search capability. To test the performance, it is applied to solve the optimal coverage problem of Wireless Sensor Network (WSN). Simulation results show it is effective when compared with the standard version of bat algorithm.
    No preview · Article · Jan 2015 · International Journal of Wireless and Mobile Computing

Publication Stats

1k Citations
255.41 Total Impact Points


  • 2002-2016
    • Tongji University
      • • Key Laboratory of Water Environment of Yangtze River
      • • College of Environmental Science and Engineering
      • • Department of Control Science and Engineering
      • • Department of Environmental Engineering
      • • College of Electronics and Information Engineering
      Shanghai, Shanghai Shi, China
  • 2015
    • Xi'an Jiaotong University
      • State Key Laboratory for Manufacturing Systems Engineering
      Ch’ang-an, Shaanxi, China
    • Shaanxi University of Science and Technology
      Syanyan, Shaanxi, China
  • 2014
    • Shaanxi Coal Research Institute of Chemical Technology Co., Ltd
      镜岭, Zhejiang Sheng, China
    • Harbin Medical University
      • Department of Biochemistry and Molecular Biology
      Charbin, Heilongjiang Sheng, China
  • 2013-2014
    • Beijing Technology and Business University
      Peping, Beijing, China
  • 2011-2014
    • Second Military Medical University, Shanghai
      Shanghai, Shanghai Shi, China
    • Tohoku University
      • Department of Applied Chemistry
  • 2010
    • Yunnan Agricultural University
      Panlong, Shaanxi, China