White Shark Research Articles

Long‐term tracking captures the timing of ontogenetic niche shifts in northeast Pacific white sharks

AbstractOntogenetic changes in area use, habitat use, and trophic interactions play an important role in the ecology, demography, and ultimately population dynamics of many species. Assumed to be driven by shifting life‐history requirements, trophic niche shifts in white sharks (Carcharodon carcharias) are well documented, but the timing of the spatial niche shift that is hypothesized to occur with the trophic niche shift remains poorly understood. To document how fine‐scale area use varies as sharks age and the timing of the ontogenetic spatial shift of this top predator, we tracked individual white sharks tagged as young‐of‐the‐year or young juveniles over multiple years. Using data from juvenile white sharks detected over multiple years in a nursery habitat with a high‐density receiver array, we found no difference in area use with age. However, using a coast‐wide receiver array including nursery and adult habitat, we found the probability of detecting a juvenile white shark in nursery habitat decreased with age, with a concurrent increasing probability of detection in adult habitat. As the conservation and management of this species relies on understanding nursery habitat use and age‐related movements, data presented here address an important knowledge gap for the understudied juvenile to subadult life stages and the ontogenetic habitat shift of this species.

Temporal and oceanographic factors differentially affect two size classes of white shark at a Southern California aggregation site

Ontogenetic habitat shifts are a common feature of many marine species, including sharks, which face conservation threats when their distributions overlap with human resource extraction and habitat modification. White sharks Carcharodon carcharias, for example, exhibit a distinctly coastal phase as juveniles, with a limited distribution compared to the basin-scale range of adults. Using an unoccupied aerial vehicle (UAV), we studied a coastal aggregation site within a Southern California Bight nursery area to determine how fine-scale temporal and oceanographic factors affect white sharks at different developmental stages. White shark density, as measured via UAV, was highly variable across time of day and day of year, with modest variation across years. Typically, more sharks were observed in the late afternoon hours. Sharks, especially those <3 m total length, were observed more often during periods of colder seafloor temperatures, potentially reflecting avoidance of these colder, deeper waters by more cold-intolerant smaller white sharks. Alternate models incorporating sea surface temperature showed a very small but significant association between surface temperatures and <3 m total length white sharks for the months we surveyed, but no such association for larger sharks. There were no or only modest effects of visibility, swell height, chl a levels, sea state, and tidal height on UAV-observed shark density. Understanding how temporal patterns and oceanographic predictors of density change over time as well as how shark ontogeny interacts with these factors can help us to better understand how this species uses coastal habitats and predict when they may be more likely to share marine space with humans.

A Novel Hybrid Approach for Remaining Useful Life (RUL) and Short-Term Capacity Prediction of Batteries

Lithium-ion battery management requires an accurate determination of the batteries’ remaining usable lives. A novel hybrid method used for the RUL and short-term capacity prediction of batteries is presented in this manuscript. The proposed technique is combined with a White Shark Optimizer (WSO) with the Multi-kernel Support Vector Machine (MSVM); therefore, it is called the WSO-MSVM technique. The major goal of this WSO-MSVM method is to attain effective future capacities and RUL forecast for the Lithium-Ion Battery (LIB) with reliable management of uncertainty. The hybrid technique solves the difficulty of forecasting the RUL of LIB. This proposal trains the WSO-MSVM model using the LIB data. The trained model is utilized to forecast the capacity and RUL of LIBs. In this proposed system, capacity, current, and voltage are considered in the discharge operation. The proposed technique validates good reliability and prediction accuracy with this suitable mechanism. Compared to the existing techniques like artificial neural network (ANN), ant lion optimizer-optimized artificial neural network, and adaptive network-based fuzzy inference system, the proposed technique shows fewer errors under charge and discharge conditions. In addition, the uncertainty intervals of the proposed WSO-MSVM technique for the predicted RUL may include the actual remaining life of the battery. The proposed technique’s charging error is lower the other exciting methods.

Correction to Effective number of white shark (Carcharodon carcharias, Linnaeus) breeders is stable over four successive years in the population adjacent to eastern Australia and New Zealand

Correction to Effective number of white shark (<i>Carcharodon carcharias</i>, Linnaeus) breeders is stable over four successive years in the population adjacent to eastern Australia and New Zealand

Thermo-elastic vibration analysis and optimization of a nanoresonator composed of a coupled nanotube system for acoustic liner application using the hybrid deep neural network–based white shark algorithm

This study explores the potential of nanoresonator systems composed of coupled nanotubes with graphene nanoparticles for enhancing the performance of acoustic liners in aircraft engines. The objective of this study is to develop an analytical model and predict its behavior under various conditions. The acoustic liners consist of perforated metal sheets and honeycomb cavities, which are essential for noise reduction in aircraft engines. The model is tested for variations in natural frequency, mode number (m), size effects (e0a), viscous constant (C), temperature (T), localness factor (L), and stiffness constant (K). A hybrid deep neural network–based white shark algorithm (DNN-WSA) is used to predict and optimize the performance of nanoresonator-coupled nanotube systems. Four theories were compared, such as wave propagation theory, nonlocal elasticity theory, polynomial eigenvalue approach, and governing equations with respect to natural frequencies in nanoresonator-coupled nanotube systems. The wave propagation theory yielded the lowest natural frequency, which was selected for detailed analysis. The optimized values of size effect of 2 nm, temperature of 5 K, and frequency of 1.971975 THz were obtained. When C = 0.3, K = 10, T = 300, and L = 10×e−9, the root mean square error (RMSE) value is 0.8421, which indicates improved predictive performance as it continues to decrease. The study’s findings showed that changes in viscous constants impact natural frequencies, while size effects have a minor influence. Temperature variations also affect natural frequencies, with higher temperatures leading to higher frequencies. The optimized model demonstrates enhanced predictive performance, which contributes to a better understanding of nanoresonator systems and their application in noise reduction for aircraft engines.

A new and effective directional overcurrent relay coordination approach for IIDG-based distribution networks using different setting groups for peak and off-peak demand periods

Directional overcurrent relays (DOCRs) must be properly coordinated to avoid vulnerabilities in the protection of distribution systems. Although most researchers have focused on changes in fault currents caused by distributed generation units (DGs), changes in load currents are also important. Due to the stochastic nature of load demand and output power of renewable-based DGs, load current magnitudes can change significantly and reach high values throughout the day. Therefore, to avoid maloperation, high pickup current settings for DOCRs must be selected. However, at this time, protection coordination may become ineffective. This paper proposes a novel DOCR coordination strategy for inverter-interfaced DG (IIDG)-based distribution systems by assigning different setting groups to each DOCR for the peak and off-peak loading periods of the day and using a realistic approach to determine maximum load currents. The aim is to achieve high effectiveness in DOCR coordination by lowering selectable pickup settings. To obtain the optimal setting groups, a new variant of the white shark optimizer is developed and used. The proposed approach reduces the total operating time of relay pairs by up to 24.5 % and 21.5 % for the IEEE 14-bus and IEEE 30-bus distribution systems, respectively, compared to the traditional coordination approach.

Three-dimensional shape of natural riblets in the white shark: relationship between the denticle morphology and swimming speed of sharks.

The ridges of the dermal denticles of migratory sharks have inspired riblets to reduce the frictional drag of a fluid. In particular, the dermal denticles of white sharks (Carcharodon carcharias) are characterized by a high middle ridge and low side ridges. The detailed morphology of their denticles and their variation along the body, however, have never been investigated. Moreover, the hydrodynamic function of high-low combinations of ridges is unknown. In this article, the ridge spacings and heights of the white shark denticles were three-dimensionally quantified using microfocus X-ray computed tomography. Then, the swimming speed at which the ridges would reduce drag was hydrodynamically calculated with a flat plate body model and previous riblet data. High ridges with a large spacing were found to effectively reduce drag at a migration speed of 2.3 m s-1, while adjacent high and low ridges with a small spacing reduced drag at a burst hunting speed of 5.1 m s-1. Moreover, the above hydrodynamic calculation method was also applied to the shortfin mako shark and an extinct giant shark (called megalodon) with known ridge spacings, resulting in the estimated hunting speeds of 10.5 m s-1and 5.9 m s-1, respectively.

First evidence of white sharks, Carcharodon carcharias, in the tongue of the ocean, central Bahamas

The white shark, Carcharodon carcharias, is an iconic apex predator, playing an important ecological role across its range. Persistent bycatch and overfishing led to white shark declines, but recent studies in the North Western Atlantic (NWA) revealed evidence for regional recovery, and highlighted the importance of Southeastern Florida and the Gulf of Mexico as overwintering grounds for maturing white sharks. However, despite its proximity to Florida and comparably productive habitats, records of white sharks in The Bahamas are extremely rare, with a comprehensive survey of sightings and captures describing only one white shark between 1800 - 2010. Here, we reveal acoustic tracking detections of ten white sharks from 2020 - 2024 along the western edge of the Tongue of the Ocean off Central Andros Island, The Bahamas. White sharks were originally tagged off the coast of the United States and Canada, and detected off Andros Island, The Bahamas from November-May. White sharks were detected along the drop-off zone of the reef at ca. 25 m, exclusively between dusk and dawn, with the number of detections suggesting transient behavior. These findings expand our knowledge of white shark distribution in the NWA, highlighting data gaps in The Bahamas and underlining the importance of collaborative protective measures for species recovery.

Genome analysis reveals three distinct lineages of the cosmopolitan white shark

The white shark (Carcharodon carcharias) (Linnaeus, 1758), an iconic apex predator occurring in all oceans,1,2 is classified as Vulnerable globally3-with global abundance having dropped to 63% of 1970s estimates,4-and as Critically Endangered in Europe.5 Identification of evolutionary significant units and their management are crucial for conservation,6 especially as the white shark is facing various but often region-specific anthropogenic threats.7,8,9,10,11 Assessing connectivity in a cosmopolitan marine species requires worldwide sampling and high-resolution genetic markers.12 Both are lacking for the white shark, with studies to date typified by numerous but geographically limited sampling, and analyses relying largely on relatively small numbers of nuclear microsatellites,13,14,15,16,17,18,19 which can be plagued by various genotyping artefacts and thus require cautious interpretation.20 Sequencing and computational advances are finally allowing genomes21,22,23 to be leveraged into population studies,24,25,26,27 with datasets comprising thousands of single-nucleotide polymorphisms (SNPs). Here, combining target gene capture (TGC)28 sequencing (89 individuals, 4,000 SNPs) and whole-genome re-sequencing (17 individuals, 391,000 SNPs) with worldwide sampling across most of the distributional range, we identify three genetically distinct allopatric lineages (North Atlantic, Indo-Pacific, and North Pacific). These diverged 100,000-200,000 years ago during the Penultimate Glaciation, when low sea levels, different ocean currents, and water temperatures produced significant biogeographic barriers. Our results show that without high-resolution genomic analyses of samples representative of a species' range,12 the true extent of diversity, presence of past and contemporary barriers to gene flow, subsequent speciation, and local evolutionary events will remain enigmatic.

Optimizing UAV Path Planning in Maritime Emergency Transportation: A Novel Multi-Strategy White Shark Optimizer

Optimizing UAV Path Planning in Maritime Emergency Transportation: A Novel Multi-Strategy White Shark Optimizer

Hybrid Photovoltaic Output Forecasting Model with Temporal Convolutional Network Using Maximal Information Coefficient and White Shark Optimizer

Accurate forecasting of PV power not only enhances the utilization of solar energy but also assists power system operators in planning and executing efficient power management. The Temporal Convolutional Network (TCN) is utilized for feature extraction from the data, while the White Shark Optimization (WSO) algorithm optimizes the TCN parameters. Given the extensive dataset and the complex variables influencing PV output in this study, the maximal information coefficient (MIC) method is employed. Initially, mutual information values are computed for the base data, and less significant variables are eliminated. Subsequently, the refined data are fed into the TCN, which is fine-tuned using WSO. Finally, the model outputs the prediction results. For testing, one year of data from a dual-axis tracking PV system is used, and the robustness of the model is further confirmed using data from single-axis and stationary PV systems. The findings demonstrate that the MIC-WSO-TCN model outperforms several benchmark models in terms of accuracy and reliability for predicting PV power.

A taste of youth: Seasonal changes in the diet of immature white sharks in eastern Australia

White sharks (Carcharodon carcharias) play a crucial ecological role, shaping ecosystems through direct predation and risk effects. On the east coast of Australia, immature white sharks are broadly distributed, inhabiting a wide range of habitats and ecosystems from temperate Tasmania to tropical North Queensland. Using stable isotopes and fatty acids of muscle and plasma, we examined the diet and habitat use of 136 immature white sharks (152–388 cm total length) captured on SMART drumlines on the East Australian coast. This facilitated the temporal assessment of white shark trophic ecology from a few weeks to approximately a year. Biochemistry of muscle samples showed that white sharks predominantly feed on low trophic level prey from coastal environments. A seasonal shift in diet was evident, with the increasing proportions of essential fatty acids in muscle tissues during spring and summer suggesting a greater consumption of high-nutrition preys during those months compared to autumn and winter. By combining stable isotope and fatty acid analysis, we gain a comprehensive understanding of immature white shark diet in eastern Australia. Our results confirm that white sharks are generalist predators that exhibit seasonal shifts in their diet. Their high use of coastal habitats reinforces the importance of these areas for foraging, which is crucial for growth and development during this critical life stage.

Personal electric deterrents can reduce shark bites from the three species responsible for the most fatal interactions

The frequency of unprovoked shark bites is increasing worldwide, leading to a growing pressure for mitigation measures to reduce shark-bite risk while maintaining conservation objectives. Personal shark deterrents are a promising and non-lethal strategy that can protect ocean users, but few have been independently and scientifically tested. In Australia, bull (Carcharhinus leucas), tiger (Galeocerdo cuvier), and white sharks (Carcharodon carcharias) are responsible for the highest number of bites and fatalities. We tested the effects of two electric deterrents (Ocean Guardian’s Freedom+ Surf and Freedom7) on the behaviour of these three species. The surf product reduced the probability of bites by 54% across all three species. The diving product had a similar effect on tiger shark bites (69% reduction) but did not reduce the frequency of bites from white sharks (1% increase), likely because the electrodes were placed further away from the bait. Electric deterrents also increased the time for bites to occur, and frequency of reactions and passes for all species tested. Our findings reveal that both Freedom+ Surf and Freedom7 electric deterrents affect shark behaviour and can reduce shark-bite risk for water users, but neither product eliminated the risk of shark bites entirely. The increasing number of studies showing the ability of personal electric deterrents to reduce shark-bite risk highlights personal protection as an effective and important part of the toolbox of shark-bite mitigation measures.

Estimating the spatial distribution of the white shark in the Mediterranean Sea via an integrated species distribution model accounting for physical barriers

AbstractConserving oceanic apex predators, such as sharks, is of utmost importance. However, scant abundance and distribution data often challenge understanding the population status of many threatened species. Occurrence records are often scarce and opportunistic, and fieldwork aimed to retrieve additional data is expensive and prone to failure. Integrating various data sources becomes crucial to developing species distribution models for informed sampling and conservation purposes. The white shark, for example, is a rare but persistent inhabitant of the Mediterranean Sea. Here, it is considered Critically Endangered by the IUCN, while population abundance, distribution patterns, and habitat use are still poorly known. This study uses available occurrence records from 1985 to 2021 from diverse sources to construct a spatial log‐Gaussian Cox process, with data‐source specific detection functions and thinning, and accounting for physical barriers. This model estimates white shark presence intensity alongside uncertainty through a Bayesian approach with Integrated Nested Laplace Approximation (INLA) and the inlabru R package. For the first time, we projected species occurrence hot spots and landscapes of relative abundance (continuous measure of animal density in space) throughout the Mediterranean Sea. This approach can be used with other rare species for which presence‐only data from different sources are available.

A hybrid technique for impact of hybrid renewable energy systems on reliability of distribution power system

A hybrid method is proposed for the effect of hybrid renewable energy systems by using photovoltaic and wind turbines based on the reliability of power system distribution. The proposed hybrid technique is the combination of the golden jackal optimization (GJO) and white shark optimization (WSO), and hence, it is named the GJO-WSO technique. The important aim of this proposed technique is to lessen the costs of the distribution system for power outages while meeting the system's needs. The GJO-WSO technique examines how renewable-energy-sources (RESs) affect the dependability of power systems (PSs). The impact of distributed generation (DG) technologies in a power system is analyzed by utilizing reliability measures like energy not supplied and expected interruption cost, (EENS, ECOST). The market pricing, wind and solar system output power, and load uncertainty are analyzed. Next, the proposed technique's performance is evaluated with other techniques. In this, the proposed technique provides a higher accuracy of 99.68 %. So, it concluded that the proposed strategy provides optimum than the present techniques.

Fisher’s perceptions on shark fisheries in Sao Tome Island (Gulf of Guinea, West Africa)

Sao Tome and Principe (STP) is a small island developing state in the Gulf of Guinea (West Africa) and is considered a global hotspot of marine biodiversity. Still, detailed information on sharks’ diversity, abundance, and respective fisheries is mainly absent. Here, we interviewed fishers from different local communities of the island of Sao Tome to characterize: i) local knowledge on shark fisheries, ii) those reliant upon these resources, and iii) their perceptions about shark populations and their importance on Sao Tome Island. A total of 111 semi-structured interviews were conducted between May 6 and June 15, 2019, in 11 fishing communities. Ninety-seven percent of fishers mentioned that sharks are present in their fishing grounds, and 98 % reported that they catch sharks. The species most identified by fishers (77 %) was the scalloped hammerhead shark (Sphyrna lewini), followed by the bluntnose sixgill shark (Hexanchus griseus; 33 %), white shark (Carcharodon carcharias; 31 %), longfin mako shark (Isurus paucus; 29 %), pigeye shark (Carcharhinus amboinensis; 27 %), and other six species (under 20 % each). Sixty-two percent of interviewees perceived sharks as a threat to their safety and livelihoods. When asked if sharks should be protected, 59 % of fishers agreed, while 40 % did not consider it necessary. Common reasons in support of protection were that sharks were disappearing (23 %), important for ocean health (9 %), and overfished (5 %). Most fishers (89 %) noticed shark abundance changes, decreasing over the past 15 years. Regarding the underlying causes, the most common response was the increase in the fishing pressure from international fishing fleets (72 %). We argue that raising awareness and building capacity close to local communities on sharks' essential role and importance will be fundamental to supporting future conservation measures, as misinformation and prejudice against sharks are widespread.

Can biochemical tracers reveal ontogenetic trophic shift and individual prey selection in white sharks from Guadalupe Island, Northeast Pacific?

Refining the role of apex predators in marine food webs is a necessary step in predicting the consequences of their global decline under the footprint of fishing activities. White sharks (Carcharodon carcharias) are vulnerable predators, performing large migrations and able to forage on a variety of prey in different habitats. In the Northeast Pacific, juvenile and adult white sharks are found seasonally at the same aggregation sites, such as Guadalupe Island off Mexico. While adults are thought to target local pinniped colonies, very few predator-prey interactions have been documented and the diet of juveniles in this area remains poorly understood. Here we used carbon/nitrogen stable isotopes and fatty acids to characterize the trophic ecology of white sharks at Guadalupe Island. In contrast to the ontogenetic trophic shift paradigm, we detected no influence of size on muscle stable isotope and fatty acid composition, revealing no significant dietary variation between juvenile and adult sharks. Stable isotopes did not allow definitive conclusions to be drawn regarding the diet of white sharks at Guadalupe Island, due to significant variability in the contribution of different potential prey depending on the trophic discrimination factors used. However, most sharks were rich in polyunsaturated fatty acids (such as long-chain omega 3), suggesting a local diet of mainly pelagic prey (potentially large fish or cephalopods). A few individuals appeared to show recent consumption of pinnipeds, with higher proportions of saturated and monounsaturated fatty acids. These individual differences in fatty acid composition could reflect an ecological trade-off between consumption of prey rich in fat (marine mammals) versus prey rich in polyunsaturated fatty acids (pelagic prey), respectively meeting the energetic and physiological needs of white sharks. Although ontogenetic trophic changes were not able to be discerned, our results provide new insights into the physiological drivers of predator-prey interactions, which can benefit the definition of conservation strategies in a changing ocean.

DIGITAL INVESTIGATION OF LAMNIFORM SHARK VERTEBRAE FROM THE SIBILLINI MTS. (NORTHERN APENNINES, ITALY)

During the sampling of a stratigraphic section along the shore of the Fiastra Lake (Carg Project - Sheet 313 “Camerino” of the Geological Map of Italy at 1:50 000 scale), a small rock boulder with partially exposed bony material was discovered at the base of a small cliff at the northern termination of the Sibillini Mts. In this area, the classical facies of Umbria-Marche stratigraphic succession are well exposed. The Oligocene-Miocene portion of the succession is represented by the ~200 m-thick Scaglia Cinerea Formation, passing upwards to the ~100 m-thick Bisciaro Formation. The microfossil assemblage has allowed the specimen to be constrained to the lower Burdigalian. The skeletal remains were examined using a CT-SCAN, a non-invasive method that has proven to be highly performing. The analysis revealed some articulated vertebrae, deformed by lithostatic compaction, which are attributed to a shark of the Order Lamniformes. Subsequently, the vertebrae were digitally isolated, extracted from the surrounding matrix, and rendered into three-dimensional prints. Through digital retro-deformation, the body length of the lamniform shark was estimated to be approximately 4 metres. Further considerations on the vertebrae allowed us to infer that the studied shark had similarities to either Isurus oxyrinchus Rafinesque, 1810 or Carcharodon carcharias Linnaeus, 1758. The development of a dead-fall microbial community likely facilitated the preservation of the vertebrae. The studied specimen represents the first occurrence of a lamniform shark in the Lower Miocene of the Umbria-Marche Domain and represents one of the very rare recorded occurrences of lamniforms from the Lower Miocene of Italy.

Who bit the boat? New DNA collection and genomic methods enable species identification in suspected shark-related incidents

Species identification following shark-related incidents is critical for effective incident management and for collecting data to inform shark-bite mitigation strategies. Witness statements are not always reliable, and species identification is often ambiguous or missing. Alternative methods for species identification include morphological assessments of bite marks, analysis of collected teeth at the scene of the incident, and genetic approaches. However, access to appropriate collection media and robust genetic assays have limited the use of genetic technologies. Here, we present a case study that facilitated a unique opportunity to compare the effectiveness of medical gauze readily available in first-aid kits, and forensic-grade swabs in collecting genetic material for shark-species identification. Sterile medical gauze and forensic-grade swabs were used to collect transfer DNA from the bite margins on a bitten surf ski which were compared to a piece of shark tissue embedded along the bite margin. Witness accounts and the characteristics of the bite mark impressions inferred the involvement of a Carcharodon carcharias (white shark). The morphology of a tooth found on the boat that picked up the surf ski, however, suggested it belonged to an Orectolobus spp. (wobbegong). Genetic analysis of DNA transferred from the shark to the surf ski included the application of a broad-target nested PCR assay followed by Sanger sequencing, with white shark contribution to the ‘total sample DNA’ determined with a species-specific qPCR assay. The results of the genetic analyses were congruent between sampling methods with respect to species identification and the level of activity inferred by the donor-specific DNA contribution. These data also supported the inferences drawn from the bite mark morphology. DNA from the recovered tooth was PCR amplified with a wobbegong-specific primer pair designed for this study to corroborate the tooth’s morphological identification. Following the confirmation of gauze used for sampling in the case study event, two additional isolated incidents occurred and were sampled in situ using gauze, as typically found in a first-aid kit, by external personnel. DNA extracted from these gauze samples resulted in the identification of a white shark as the donor of the DNA collected from the bite marks in both instances. This study, involving three incidents separated by time and location, represents the seminal application of gauze as a sampling media after critical human-shark interactions and strongly supports the practical implementation of these methods in the field.

Hand Gestures Recognition Model Using Adaptive Feature Extraction with Attention-Based Hybrid Deep Learning via Optimization Strategy

Research on continuous hand gesture recognition is motivated by applications of deaf people to provide effective communication between one another. Numerous techniques are adapted for effectively identifying the hand gesture. Moreover, the collection of data becomes a challenging task in the existing models. In some instances, hand gesture in low-resolution images becomes a complicated task. In this research work, a deep learning-based hand gesture detection model is designed using hand data points to uncover patterns that are used to convey information. Initially, hand gesture images are obtained from public sources. The collected inputs are preprocessed through Contrast-Limited Adaptive Histogram Equalization and filtering to eliminate the unnecessary blurs in the images. The preprocessed images undergo hand segmentation using four methods color space transformation, skin color detection, active contour, and morphological operation. The segmented image is subjected to data point feature extraction, where the Adaptive Weighted Scale-Invariant Feature Transform is utilized for further enhancement. The hand data point-extracted features are given to the recognition of hand gestures with the support of an attention-based hybrid network, where the Attention-based Hybrid 1D Convolutional Neural Network with Recurrent Neural Network recognizes the hand gestures from the hand data points. In the hybridization network, the values are optimized with the help of the investigated Adaptive Dandelion White Shark Optimizer to enhance recognition effectiveness. The test results are validated with the existing hand gesture recognition models using diverse evaluation metrics. The findings of the recommended method show 97% and 99% in terms of accuracy and NPV. Thus, the developed model is validated to outperform significant performance rather than the existing models.