Local Vector Research Articles

Impact of ecological migration village construction on vector mosquito and mosquito-borne disease in the southern Yunnan Province, China

To evaluate the influence of ecological migration village construction on mosquito vector populations and mosquito-borne diseases in southern Yunnan Province. Two vicinal villages in Mengla County, the southern part of Yunnan Province, a native village, and a newly built village, were selected as study sites. Malaria and Japanese Encephalitis vector mosquito population divergence between the two villages were studied. Malaria and Japanese Encephalitis (JE) cases in the two villages were also compared. Anopheles minimus was the dominant population in houses in the newly built village, and An. jeyporiensis dominated the native village. Accordingly, there were nine malaria cases in the new village compared with zero cases in the native village. Culex tritaeniorhynchus, the chief JE vector in the study area, displayed no difference between the two villages; however, there was a higher density of the local secondary JE vector (Cx. pseudovishnui) in the native village than in the new one. The JE cases in the villages corresponded to zero. From the vector-borne disease perspective, our results suggest that local community should pay more attention to malaria and An. minimus during the construction of an ecological migration village in the new Chinese Western Developing Plan (CWDP) in southern Yunnan Province.

Design of distributed event‐triggered states and unknown disturbances observers for time‐varying delay interconnected systems

SummaryThis article considers the problem of designing distributed event‐triggered states and unknown disturbances observers for a class of nonlinear interconnected systems where the local state vectors are affected by unknown delays and the nonlinear function satisfying the Lipschitz condition. Distributed observers are designed based on the local input vector and both the local and remote output vectors. Different from previously distributed observers for interconnected systems where the local and remote output vectors are updated continuously, the one in this article uses only information on the local and remote output vectors updating at triggering instants of proposed event‐triggered mechanisms. This indicates that the proposed method in this article is better than the existing ones in saving communication resources while still keeping an acceptable estimation performance. Sufficient conditions for the existence of the proposed distributed observers are established and are formed in a convex optimization problem which can be easily solved by using the MATLAB LMI Control Toolbox. Finally, a numerical example is given to confirm the effectiveness and advantages of the proposed method.

Three dimensional interface normal prediction for Volume-of-Fluid method using artificial neural network

In the numerical simulations of multi-phase flow using Volume-of-Fluid (VOF) method, the calculation of the interface normal is a crucial point. In this paper, a machine learning method is used to develop an artificial neural network (ANN) model to make more accurate prediction of the local normal vector from neighboring volume fractions. Spherical surfaces with different radii are intersected with a structural background grid to generate 84328 groups of data: 3×3×3 neighboring volume fractions are used as input, and normal vector as output. Using 90% data as training dataset, the ANN model is well trained by optimizing the number of hidden layers and the number of neurons on each layer. Using the remaining 10% data, normal predictions are made using ANN-VOF and the most used YOUNG and HEIGHT-FUNCTION methods. The RMSE of the ANN-VOF/YOUNG/ HEIGHT-FUNCTION methods are 0.008/0.022/0.045 respectively. In the reconstruction of a sinusoidal surface, the MSE of the ANN-VOF/YOUNG/ HEIGHT-FUNCTION methods are 0.008/0.018/0.041. It is demonstrated that the ANN-VOF method has better performance for interface normal prediction. The proposed method has a simple computational logic and does not need to deal with complex geometric topology, which lays the foundation for application in other more complex grids.

Virome release of an invasive exotic plant species in southern France.

The increase in human-mediated introduction of plant species to new regions has resulted in a rise of invasive exotic plant species (IEPS) that has had significant effects on biodiversity and ecosystem processes. One commonly accepted mechanism of invasions is that proposed by the enemy release hypothesis (ERH), which states that IEPS free from their native herbivores and natural enemies in new environments can outcompete indigenous species and become invasive. We here propose the virome release hypothesis (VRH) as a virus-centered variant of the conventional ERH that is only focused on enemies. The VRH predicts that vertically transmitted plant-associated viruses (PAV, encompassing phytoviruses and mycoviruses) should be co-introduced during the dissemination of the IEPS, while horizontally transmitted PAV of IEPS should be left behind or should not be locally transmitted in the introduced area due to a maladaptation of local vectors. To document the VRH, virome richness and composition as well as PAV prevalence, co-infection, host range, and transmission modes were compared between indigenous plant species and an invasive grass, cane bluestem (Bothriochloa barbinodis), in both its introduced range (southern France) and one area of its native range (Sonoran Desert, Arizona, USA). Contrary to the VRH, we show that invasive populations of B. barbinodis in France were not associated with a lower PAV prevalence or richness than native populations of B. barbinodis from the USA. However, comparison of virome compositions and network analyses further revealed more diverse and complex plant-virus interactions in the French ecosystem, with a significant richness of mycoviruses. Setting mycoviruses apart, only one putatively vertically transmitted phytovirus (belonging to the Amalgaviridae family) and one putatively horizontally transmitted phytovirus (belonging to the Geminiviridae family) were identified from B. barbinodis plants in the introduced area. Collectively, these characteristics of the B. barbinodis-associated PAV community in southern France suggest that a virome release phase may have immediately followed the introduction of B. barbinodis to France in the 1960s or 1970s, and that, since then, the invasive populations of this IEPS have already transitioned out of this virome release phase, and have started interacting with several local mycoviruses and a few local plant viruses.

Recognition of Angry and Happy Facial Expressions with Local Binary Pattern and Support Vector Machine

Looks are a huge sort of nonverbal correspondence for getting a handle on a singular's opinions and sentiments. Look affirmation has various potential applications, including security, tutoring, and prosperity systems. The justification for this assessment is for a look affirmation system using area twofold model and sponsorship vector machine techniques. It is typical that this structure can perceive two kinds of sentiments, to be explicit angry and delighted to get the right assumption. First accumulate fundamental data and assistant data from Kaggle and phone cameras, second preprocessing data with grayscale and resizing, third surface features using Area equal model extraction, fourth assist vector with machining about look request used, finally structure evaluation considering precision, exactness, survey, and F-1 worth. The results show that the look affirmation system works honorably on area matched model and sponsorship vector machine. On this investigation dataset, support vector machine gathering on direct part has favored execution over winding reason ability segment. The most significant precision was achieved with the straight part at 86.25%. This study assumes that the look affirmation structure can work outstandingly with neighborhood matched model and sponsorship vector machine. The straight part shows better execution on this investigation dataset. This assessment can be also advanced by adding more looks, incorporate extraction methods, and plan.

An optical-scan method for measuring the as installed surface port incidence angles for flush air data sensing (FADS) systems

The Flush Air Data Sensing (FADS) System, where air data are inferred from non-intrusive surface pressure measurements, uses natural contours of the vehicle forebody, wing leading edge, or probe. Although multiple methods have been developed to derive airdata from the sensed pressure matrix, all methods rely on accurate knowledge of local surface contours at the port locations. One of the most well-developed solution methods curve-fits the surface pressure distribution against the associated surface incidence angles using a quasi-Newtonian model. The well-known "Triples" algorithm extracts airdata from the curve-fit model. This solution method requires precise knowledge of as-installed incidence angles, i.e. the angles between the surface normal and the longitudinal axis of the vehicle. This study investigates the feasibility and accuracy of using an inexpensive optical-scanning system to measure the in-situ FADS pressure ports surface incidence angles. Here, two legacy 3-D printed probe shapes, as previously tested during a series of very low-speed wind tunnel tests, were used to develop and evaluate this method. The shapes 1) a hemispherical head cylindrical forebody, and 2) a Rankine-Body, were scanned along the longitudinal axis and the resulting point-cloud was edited using open-source software to generate three concentric "loops" surrounding each surface port. Each annular loop was assumed as co-planar with the surface port, and the singular-value decomposition (SVD) was used calculate the local surface gradient vector from the null-space solution. From the resulting gradient vector, geometric relationships calculate the port's polar coordinates including the surface incidence angle. For both body contours the resulting calculations are compared to the "known" design surface angles as prescribed for the 3-D prints. Error plots are presented for each individual ring-set, and for the collected set using all three ring together. For the collected data sets, the incidence angle calculations are accurate to within a quarter-degree.

The Alpha-proton Differential Flow in the Alfvénic Young Solar Wind: from Sub-Alfvénic to Super-Alfvénic

Data obtained from Parker Solar Probe (PSP) since 2021 April have shown the first in situ observation of the solar corona, where the solar wind is formed and accelerated. Here, we investigate the alpha-proton differential flow and its characteristics across the critical Alfvén surface (CAS) using data from PSP during encounters 8–10 and 12–13. We first show the positive correlation between the alpha-proton differential velocity and the bulk solar wind speed at PSP encounter distances. Then we explore how the characteristics of the differential flow vary across the CAS and how they are affected by Alfvénic fluctuations including switchbacks. We find that the differential velocity below the CAS is generally smaller than that above the CAS, and the local Alfvén speed well limits the differential speed both above and below the CAS. The deviations from the alignment between the differential velocity and the local magnetic field vector are accompanied by large-amplitude Alfvénic fluctuations and decreases in the differential speed. Moreover, we observe that V α p increases from M A < 1 to M A ≃ 2 and then starts to decrease, which suggests that alphas may remain preferentially accelerated well above the CAS. Our results also reveal that in the sub-Alfvénic solar wind both protons and alphas show a strong correlation between their velocity fluctuations and magnetic field fluctuations, with a weaker correlation for alphas. By contrast, in the super-Alfvénic regime the correlation remains high for protons, but is reduced for alphas.

Local projections vs. VARs: Lessons from thousands of DGPs

We conduct a simulation study of Local Projection (LP) and Vector Autoregression (VAR) estimators of structural impulse responses across thousands of data generating processes, designed to mimic the properties of the universe of U.S. macroeconomic data. Our analysis considers various identification schemes and several variants of LP and VAR estimators, employing bias correction, shrinkage, or model averaging. A clear bias–variance trade-off emerges: LP estimators have lower bias than VAR estimators, but they also have substantially higher variance at intermediate and long horizons. Bias-corrected LP is the preferred method if and only if the researcher overwhelmingly prioritizes bias. For researchers who also care about precision, VAR methods are the most attractive—Bayesian VARs at short and long horizons, and least-squares VARs at intermediate and long horizons.

Genetic structure of &lt;i&gt;Ehrlichia ruminantium&lt;/i&gt; based on Multilocus Sequence Typing: particularities of strains from West-Africa

Ehrlichia ruminantium is the tick-borne rickettsia causing heartwater to wild and domestic ruminants. Previously, Multilocus Sequence Typing of this pathogen (MLST) highlighted the co-circulation of two genotypic groups within nearby villages from Burkina Faso where vaccination assays had been previously recurrently performed. In the present study the laboratory strains that had been involved in vaccination assays, which evidenced their close relationships with strains that were later involved in local outbursts, were genotyped. Characterization of the bacterium genetic diversity was extended to four distant Beninese localities where no vaccination assays had ever been performed, through sampling of N=500 specimens of the local tick vector, Amblyomma variegatum. This led evidencing an even higher frequency of new multilocus MLST genotypes in Benin than in Burkina Faso, 93% of the Beninese genotypes included at least one new private allele (i.e., no detected elsewhere), while this was only the case of 80% bacteria genotypes sampled in Burkina Faso. Investigating the genetic structure of the bacterium across the Africa continent revealed a reduction of its diversity in the eastern and southern part of the continent relatively to West Africa. As the bacterial genetic diversity currently remains highest in West Africa than anywhere else in the continent, this area remains optimal for the development and/or testing of vaccines against heartwater.

Nfe2l3 promotes neuroprotection and long-distance axon regeneration after injury in vivo

Nuclear factor erythroid 2 like (Nfe2l) gene family members 1–3 mediate cellular response to oxidative stress, including in the central nervous system (CNS). However, neuronal functions of Nfe2l3 are unknown. Here, we comparatively evaluated expression of Nfe2l1, Nfe2l2, and Nfe2l3 in singe cell RNA-seq (scRNA-seq)-profiled cortical and retinal ganglion cell (RGC) CNS projection neurons, investigated whether Nfe2l3 regulates neuroprotection and axon regeneration after CNS injury in vivo, and characterized a gene network associated with Nfe2l3 in neurons. We showed that, Nfe2l3 expression transiently peaks in developing immature cortical and RGC projection neurons, but is nearly abolished in adult neurons and is not upregulated after injury. Furthermore, within the retina, Nfe2l3 is enriched in RGCs, primarily neonatally, and not upregulated in injured RGCs, whereas Nfe2l1 and Nfe2l2 are expressed robustly in other retinal cell types as well and are upregulated in injured RGCs. We also found that, expressing Nfe2l3 in injured RGCs through localized intralocular viral vector delivery promotes neuroprotection and long-distance axon regeneration after optic nerve injury in vivo. Moreover, Nfe2l3 provided a similar extent of neuroprotection and axon regeneration as viral vector-targeting of Pten and Klf9, which are prominent regulators of neuroprotection and long-distance axon regeneration. Finally, we bioinformatically characterized a gene network associated with Nfe2l3 in neurons, which predicted the association of Nfe2l3 with established mechanisms of neuroprotection and axon regeneration. Thus, Nfe2l3 is a novel neuroprotection and axon regeneration-promoting factor with a therapeutic potential for treating CNS injury and disease.

An Algorithm Based on Non-Negative Matrix Factorization for Detecting Communities in Networks

Community structure is a significant characteristic of complex networks, and community detection has valuable applications in network structure analysis. Non-negative matrix factorization (NMF) is a key set of algorithms used to solve the community detection issue. Nevertheless, the localization of feature vectors in the adjacency matrix, which represents the characteristics of complex network structures, frequently leads to the failure of NMF-based approaches when the data matrix has a low density. This paper presents a novel algorithm for detecting sparse network communities using non-negative matrix factorization (NMF). The algorithm utilizes local feature vectors to represent the original network topological features and learns regularization matrices. The resulting feature matrices effectively reveal the global structure of the data matrix, demonstrating enhanced feature expression capabilities. The regularized data matrix resolves the issue of localized feature vectors caused by sparsity or noise, in contrast to the adjacency matrix. The approach has superior accuracy in detecting community structures compared to standard NMF-based community detection algorithms, as evidenced by experimental findings on both simulated and real-world networks.

Modeling Aircraft Fuel Jettison Using Smoothed Particle Hydrodynamics on Finite-Volume Meshes

Weakly compressible smoothed particle hydrodynamics is used to investigate aircraft fuel jettison using a single-phase model. Fuel simulations are coupled to the aircraft computational fluid dynamics flowfield using cell containment checks on the finite-volume mesh to locate any smoothed particle hydrodynamics (SPH) particle within the mesh, after which the local flow velocity vector is retrieved and then used to apply an approximate aerodynamic force to the SPH particle based on a continuum correction to discrete droplet calculations. Further downstream, the SPH simulation may be continued, or a switch may be made to implicit particle tracking (IPT) in order to accelerate the simulation. Comparison to IPT results shows that a fluid model of the initial continuum breakup of the jet is required, but following this transition to IPT is reasonable to reduce computation time. Models are validated against volume of fluid (VOF) simulations, with the runtime of the proposed model being approximately 100 times less than the VOF, and good qualitative agreement is also found compared to recorded flight results.

Diagnosing Faults in Rolling Bearings of an Air Compressor Set Up Using Local Mean Decomposition and Support Vector Machine Algorithm

Diagnosing Faults in Rolling Bearings of an Air Compressor Set Up Using Local Mean Decomposition and Support Vector Machine Algorithm

Quantitative analysis of risk assessment indicators for re-introduction of imported malaria in China

To quantitatively analyze the risk indicators of re-introduction of imported malaria in China and their weighting coefficients, so as to investigate the difference in the contribution of risk indicators included in the current risk assessment framework for re-introduction of imported malaria in China to the risk assessment of re-introduction of imported malaria. Publications pertaining to the risk assessment framework for re-introduction of imported malaria in China that reported the risk indicators and their weighting coefficients were retrieved in PubMed, Web of Science, CNKI, Wanfang Data, and VIP with terms of "malaria", "re-introduction/re-transmission/re-establishment", "risk assessment/risk evaluation/risk prediction" from the inception of the database through 3 August 2023, and literature search was performed in Google Scholar to ensure the comprehensiveness of the retrieval. Basic characteristics of included studies were extracted using pre-designed information extraction forms by two investigators, and data pertaining to risk indicators of re-introduction of imported malaria were cross-checked by these two investigators. The risk indicators included in the risk assessment framework for re-introduction of imported malaria in China and their weighting coefficients were visualized with the Nightingale's rose diagrams using the software R 4.2.1, and the importance of risk indictors was evaluated with the frequency of risk indicators included in the risk assessment framework and the ranking of weighting coefficients of risk indicators. In addition, the capability of risk indicators screened by different weighting methods was compared by calculating the ratio of the maximum to the minimum of the weighting coefficients of the risk indicators screened by different weighting methods. A total of 2 138 publications were retrieved, and following removal of duplications and screening, a total of 8 publications were included in the final analysis. In these 8 studies, 8 risk assessment frameworks for re-introduction of imported malaria in China and 52 risk indicators of re-introduction of imported malaria were reported, in which number of imported malaria cases (n = 8) and species of malaria vectors were more frequently included in the risk assessment frameworks (n = 8), followed by species of imported malaria parasites (n = 6) and population density of local malaria vectors (n = 6), and species of local malaria vectors (n = 6), number of imported malaria cases (n = 5) and species of imported malaria parasites had the three highest weighting coefficients (n = 4). The weighting methods included expert scoring method, combination of expert scoring method and analytic hierarchy process, and combination of expert scoring method and entropy weight method in these 8 studies, and the ratios of the maximum to the minimum of the weighting coefficients of the risk indicators screened by the expert scoring method were 1.143 to 2.241, while the ratios of the maximum to the minimum of the weighting coefficients of the risk indicators screened by combination of the expert scoring method and analytic hierarchy process were 34.970 to 162.000. Number of imported malaria cases, species of imported malaria parasites, species of local malaria vectors and population density of local malaria vectors are core indicators in the current risk assessment framework for re-introduction of imported malaria in China. Combination of the expert scoring method and analytic hierarchy process is superior to the expert scoring method alone for weighting the risk indicators.

Focusing of linearly polarized optical vortex and a Hall effect

Polarization of a higher-order cylindrical vector beam (CVB) is known to be locally linear. The higher the beam order, the larger number of full circles the local linear polarization vector makes around the optical axis. It is also known that the CVB with radially symmetric amplitude has zero spin angular momentum (SAM) and zero orbital angular momentum (OAM) both in the initial plane and in the focal plane (because in both Cartesian components of the vector field, the angular derivative of phase is zero). We show here that near the focal plane of the CVB (i.e. before and beyond the focus), an even number of local subwavelength areas with rotating polarization vectors are generated. In addition, in the neighboring areas, the polarization vectors are rotating in the opposite directions. Thus, the longitudinal components of the SAM vector in such neighboring areas are of different sign. After passing through the focal plane, the rotation direction of the polarization vector at each point of the beam cross-section changes to the opposite one. Such a spatial separation of the left and right rotation of the polarization vectors is a manifestation of the optical spin Hall effect.

Focusing a cylindrical vector beam and the Hall effect

Polarization of a higher-order cylindrical vector beam (CVB) is known to be locally linear. The higher the beam order, the larger number of full circles the local linear polarization vector makes around the optical axis. It is also known that the CVB with radially symmetric amplitude has zero spin angular momentum (SAM) and zero orbital angular momentum (OAM) both in the initial plane and in the focal plane (because in both Cartesian components of the vector field, the angular derivative of phase is zero). We show here that near the focal plane of the CVB (i.e. before and beyond the focus), an even number of local subwavelength areas with rotating polarization vectors are generated. In addition, in the neighboring areas, the polarization vectors are rotating in the opposite directions. Thus, the longitudinal components of the SAM vector in such neighboring areas are of different sign. After passing through the focal plane, the rotation direction of the polarization vector at each point of the beam cross-section changes to the opposite one. Such a spatial separation of the left and right rotation of the polarization vectors is a manifestation of the optical spin Hall effect.

A framework to facilitate development and testing of image‐based river velocimetry algorithms

AbstractImage‐based methods have compelling, demonstrated potential for characterizing flow fields in rivers, but algorithms like particle image velocimetry (PIV) must be further tested and improved to enable more effective use of these techniques. This paper presents a framework designed for this exact purpose: Simulating Hydraulics and Images for Velocimetry Evaluation and Refinement (SHIVER). The approach involves coupling a hydrodynamic model with a synthetic particle generator to advect particles between frames, as dictated by local velocity vectors and thus construct a plausible image sequence specific to the reach of interest. The resulting time series can then be used as input to a velocimetry algorithm to compare image‐derived estimates with known (modelled) velocities to perform an exhaustive, spatially distributed accuracy assessment. As an example application of SHIVER, we examined the effects of interrogation area (IA) size, frame rate, flow velocity, and image sequence duration on the performance of a standard PIV algorithm. This analysis indicated that image‐derived velocities were generally in close agreement with those from the flow model (root mean square error &lt;10% and mean bias &lt;3%), except when small IAs were coupled with low frame rates. Velocity estimates were most accurate for the lowest modelled discharge ( at baseflow) and became less reliable as the mean flow velocity increased ( for an intermediate discharge and at bankfull). Accuracy was essentially independent of image sequence duration, implying that long occupations might not be necessary. Errors were concentrated along channel margins, where PIV‐based velocities tended to be greater than those from the flow model. Small IAs led to underpredictions of velocity, while larger IAs led to overpredictions. SHIVER is highly modular and could be updated to make use of different hydrodynamic models or image simulators. The framework could also facilitate more thorough sensitivity analyses and comparison of various velocimetry algorithms.

Multiple Anopheles species complicate downstream analysis and decision-making in a malaria pre-elimination area in southern Mozambique

BackgroundDifferent anopheline species (even within a species group/complex) can differ in their feeding and resting behaviours, which impact both malaria transmission patterns as well as the efficacy of vector control interventions. While morphological identification of sampled specimens is an important first step towards understanding species diversity and abundance, misidentification can result in the implementation of less effective vector control measures, and consequently smaller reductions in the number of local malaria cases. Focusing on southern Mozambique, a malaria pre-elimination area where malaria remains persistent, the aims of this preliminary study were to use molecular identification (CO1 and ITS2 barcoding) to (1) validate the results from the morphological identification (with a particular focus on Anopheles pharoensis and Anopheles squamosus), and (2) have a closer look at the Anopheles coustani group (which includes Anopheles tenebrosus and Anopheles ziemanni).MethodsFemale anopheline mosquitoes (n = 81) were identified morphologically and subsequently sequenced at the ribosomal DNA internal transcribed spacer region 2 (ITS2) and/or cytochrome oxidase subunit 1 (CO1) loci towards species determination.ResultsOut of the 62 specimens that were identified morphologically to species, 4 (6.5%) were misidentified. Regarding the An. coustani group, morphological identification showed that several members are present in southern Mozambique, including An. coustani sensu lato (s.l.), An. ziemanni and An. tenebrosus. However, based on both ITS2 and CO1 sequences, the exact species remains unknown for the latter two members until voucher sequences are available for comparison.ConclusionThe reason(s) for morphological misidentification of anopheline mosquitoes need to be mitigated. This is usually related to both the capacity (i.e. training) of the microscopist to identify anopheline species, and the information provided in the dichotomous identification key. As the An. coustani complex contributes to (residual) malaria transmission in sub-Saharan Africa, it may play a role in the observed persistent malaria in southern Mozambique. A better baseline characterizing of the local anophelines species diversity and behaviours will allow us to improve entomological surveillance strategies, better understand the impact of vector control on each local vector species, and identify new approaches to target those vector species.

Window size analysis in ultrasonic temperature estimation with timeshifts

In this work, ultrasonic timeshift method for temperature change estimation was investigated for 2D simulated in-silico synthetic ultrasonic signals. Digital phantom tissue was created in MATLAB environment and acoustic simulation was running on k-Wave toolbox for two different temperature conditions. First temperature distribution was assigned to tissue as uniform 37 °C. Second temperature distribution is Gaussian form with peak at tissue center as 45 °C and tails of Gaussian curve is 37 °C. Signal was analyzed with ultrasonic timeshift method for temperature change estimation. This method is based on four steps, calibration with tissue constant, finding timeshift with cross correlation algorithm, find slope of timeshift vector respect to timestep, and multiply tissue constant and slope of local timeshift vector. This multiplication gives temperature change of local point. In this work, window size of smoothing filter of timeshift vector and linear fitting to timeshift—timestep data was analyzed as parametrically with range 3λ to 10λ with a 1λ increment for both windows equally. As a result, window parameters as 5λ to 7λ give best results, maximum absolute error is 0.82 °C, 0.97 °C and 0.92 °C respectively and mean absolute error is ∼0.35 °C. As a verify, different analysis was performed on different temperature distribution with discrete two peak curves.

A reinforcement learning-based neighborhood search operator for multi-modal optimization and its applications

In this paper, a reinforcement learning-based neighborhood search operator (RLNS) is proposed for multi-modal optimization problems where the main novelties lie in the reinforcement learning-based neighborhood range selection strategy, the neighborhood subpopulation generation strategy and the local vector encirclement model. The reinforcement learning-based neighborhood range selection strategy is proposed to dynamically adjust the subpopulation size to address the issue of too many parameters to be adjusted in the multi-modal optimization algorithm based on the niching methods, while the neighborhood subpopulation generation strategy and the local vector encirclement model are designed with the hope of enhancing the individual’s ability to local exploitation to obtain more accurate solutions. To verify the effectiveness of the proposed RLNS, SSA-RLNS, PSO-RLNS and EO-RLNS are proposed by integrating the proposed RLNS with the existing sparrow search algorithm, particle swarm optimization and equilibrium optimizer. The performances of the proposed SSA-RLNS, PSO-RLNS, EO-RLNS and existing multi-modal optimization algorithms are tested in CEC2015 multi-niche benchmark functions. The experimental results show that the SSA-RLNS, PSO-RLNS and EO-RLNS could locate multiple global optimal solutions with satisfactory accuracy, which illustrate that the proposed RLNS could be successfully used to deal with multi-modal optimization problems by integrating with common population-based optimization algorithms. Finally, the SSA-RLNS is successfully applied in the inverse kinematics of robot manipulator.