Appropriate Combination of Crossover Operator and Mutation Operator in Genetic Algorithms for the Travelling Salesman Problem

Genetic algorithms(GAs)are very good metaheuristic algorithms that are suitable for solving NP-hard combinatorial optimization problems.AsimpleGAbeginswith a set of solutions represented by a population of chromosomes and then uses the idea of survival of the fittest in the selection process to select some fitter chromosomes.It uses a crossover operator to create better offspring chromosomes and thus,converges the population.Also,it uses a mutation operator to explore the unexplored areas by the crossover operator,and thus,diversifies the GA search space.A combination of crossover and mutation operators makes the GA search strong enough to reach the optimal solution.However,appropriate selection and combination of crossover operator and mutation operator can lead to a very good GA for solving an optimization problem.In this present paper,we aim to study the benchmark traveling salesman problem(TSP).We developed several genetic algorithms using seven crossover operators and six mutation operators for the TSP and then compared them to some benchmark TSPLIB instances.The experimental studies show the effectiveness of the combination of a comprehensive sequential constructive crossover operator and insertion mutation operator for the problem.The GA using the comprehensive sequential constructive crossover with insertion mutation could find average solutions whose average percentage of excesses from the best-known solutions are between 0.22 and 14.94 for our experimented problem instances.

Review of IoT and electronics enabled smart agriculture

The population increases at an exponential rate as human society advances,and pollution is increasingly depleting the availability of resources such as water and land.All these problems are thought to require the use of smart agriculture.By reducing use of chemical fertilizers and pesticides,smart agriculture could mitigate land pollution and increase the sustainability of agricultural practices while also greatly enhancing the agro-ecological environment,yield,and quality of crops.The steps to make agriculture smart are made possible through data and communication technology,which helps with automatic operation and cultivation.Moreover,advances in wireless communication protocols will bring agriculture to a more intelligent stage.This study provides an overview of IoT technology and its application in the smart agriculture industry to make crop production automatic and intelligent by assessing their architecture(IoT devices,communication technologies,and processing),their applications,and research timelines.The communication protocols that have established uses in agriculture are reviewed first in this article.Various wireless communication protocols such as WiFi,ZigBee,SigFox,LoRa,RFID,NFMI,Terahertz,and NB-IoT were summarized,and their applications in various fields were also studied.These protocols in smart agriculture can effectively and efficiently address environmental data,water saving,monitoring of animal behavior,accuracy,power efficiency,cost reduction due to low power consumption,accuracy,wide transmission,simple in operation and cost effective.The most commonly used microcontrollers are Arduino(to develop autonomous machines),Raspberry Pi(to store data),and 8-bit microcontroller(to process data).In addition,it is important to take advantage of modern communication technology to enhance crop production.This study also examines the future opportunities and trends for IoT applications in smart agriculture,along with the ongoing challenges and issues that need addressing.Furthermore,it provides crucial insights and guidance for future research and the development of IoT solutions.These advancements aim to improve agricultural productivity and quality while facilitating the transition to a more sustainable agroecological future.

A New Scheme of the ARA Transform for Solving Fractional-Order Waves-Like Equations Involving Variable Coefficients

The goal of this research is to develop a new,simplified analytical method known as the ARA-residue power series method for obtaining exact-approximate solutions employing Caputo type fractional partial differential equations(PDEs)with variable coefficient.ARA-transform is a robust and highly flexible generalization that unifies several existing transforms.The key concept behind this method is to create approximate series outcomes by implementing the ARA-transform and Taylor’s expansion.The process of finding approximations for dynamical fractional-order PDEs is challenging,but the ARA-residual power series technique magnifies this challenge by articulating the solution in a series pattern and then determining the series coefficients by employing the residual component and the limit at infinity concepts.This approach is effective and useful for solving a massive class of fractional-order PDEs.Five appealing implementations are taken into consideration to demonstrate the effectiveness of the projected technique in creating solitary series findings for the governing equations with variable coefficients.Additionally,several visualizations are drawn for different fractional-order values.Besides that,the estimated findings by the proposed technique are in close agreement with the exact outcomes.Finally,statistical analyses further validate the efficacy,dependability and steady interconnectivity of the suggested ARA-residue power series approach.

Reduced differential transform and Sumudu transform methods for solving fractional financial models of awareness

In that paper,we new study has been carried out on previous studies of one of the most important mathematical models that describe the global economic movement,and that is described as a non-linear fractional financial model of awareness,where the studies are represented at the steps following:One:The schematic of the model is suggested.Two:The disease-free equilibrium point(DFE)and the stability of the equilibrium point are discussed.Three:The stability of the model is fulfilled by drawing the Lyapunov exponents and Poincare map.Fourth:The existence of uniformly stable solutions have discussed.Five:The Caputo is described as the fractional derivative.Six:Fractional optimal control for NFFMA is discussed by clarifying the fractional optimal control through drawing before and after control.Seven:Reduced differential transform method(RDTM)and Sumudu Decomposition Method(SDM)are used to take the resolution of an NFFMA.Finally,we display that SDM and RDTM are highly identical.

Intoxication Induced by Urea Containing Diets in Broiler Chickens: Effect on Weight Gain, Feed Conversion Ratio, Hematological and Biochemical Profiles

Urea as a source of cheap non-protein nitrogen is used to adulterate fish and meat meals which are basic components of broiler diets. The present study was carried out to elucidate the effects of urea on weight gain, and hematological and biochemical profiles. A total of 48 broiler chicks were randomly allotted into 4 groups, designated Groups 1, 2, 3 and 4 of 12 birds each. Birds in Groups 2, 3 and 4 were fed on diets containing urea at the levels of 1%, 2.5% and 4%, respectively. Birds in Group 1 served as control and were not exposed to urea. Experimentation period was for 3 weeks and experiment was terminated when birds were 42 days of age. Body weight of all intoxicated birds at the various intervals was significantly decreased in comparison with that of the untreated control. Compared with control, all intoxicated broilers manifested significant (P ≤ 0.05) decrease in all hematological parameters involving erythrocytic and total leucocytic counts, Hemoglobin (Hb) and Packed Cell Volume (PCV) on a dose- and time-pattern. In comparison with the control levels, biochemical profile of the intoxicated birds disclosed significant decrease in blood glucose level and significant increase in serum uric acid, urea, Alkaline Phosphatase (ALP) and Lactate Dehydrogenase (LDH) levels. Based upon the present data, it was concluded that the addition of urea to broiler diets bears serious sequences concerning the general health condition, performance, weight gain, and hematological and biochemical profiles.

Optimization of Coronavirus Pandemic Model Through Artificial Intelligence

Artificial intelligence is demonstrated by machines,unlike the natural intelligence displayed by animals,including humans.Artificial intelligence research has been defined as the field of study of intelligent agents,which refers to any system that perceives its environment and takes actions that maximize its chance of achieving its goals.The techniques of intelligent computing solve many applications of mathematical modeling.The researchworkwas designed via a particularmethod of artificial neural networks to solve the mathematical model of coronavirus.The representation of the mathematical model is made via systems of nonlinear ordinary differential equations.These differential equations are established by collecting the susceptible,the exposed,the symptomatic,super spreaders,infection with asymptomatic,hospitalized,recovery,and fatality classes.The generation of the coronavirus model’s dataset is exploited by the strength of the explicit Runge Kutta method for different countries like India,Pakistan,Italy,and many more.The generated dataset is approximately used for training,validation,and testing processes for each cyclic update in Bayesian Regularization Backpropagation for the numerical treatment of the dynamics of the desired model.The performance and effectiveness of the designed methodology are checked through mean squared error,error histograms,numerical solutions,absolute error,and regression analysis.

Numerical Assessment of Nanofluid Natural Convection Using Local RBF Method Coupled with an Artificial Compressibility Model

In this paper,natural heat convection inside square and equilateral triangular cavities was studied using a meshless method based on collocation local radial basis function(RBF).The nanofluids used were Cu-water or Al_(2)O_(3)-water mixture with nanoparticle volume fractions range of 0≤φ≤0.2.A system of continuity,momentum,and energy partial differential equations was used in modeling the flow and temperature behavior of the fluids.Partial derivatives in the governing equations were approximated using the RBF method.The artificial compressibility model was implemented to overcome the pressure velocity coupling problem that occurs in such equations.Themain goal of this work was to present a simple and efficient method to deal with complex geometries for a variety of problem conditions.To assess the accuracy of the proposed method,several test cases of natural convection in square and triangular cavities were selected.For Rayleigh numbers ranging from 103 to 105,a validation test of natural convection of Cu-water in a square cavity was used.The numerical investigation was then extended to Rayleigh number 106,as well as Al_(2)O_(3)-water nanofluid with a volume fraction range of 0≤φ≤0.2.In a second investigation,the same nanofluids were used in a triangular cavitywith varying volume fractions to test the proposed meshless approach on non-rectangular geometries.The numerical results appear to be in agreement with those from earlier investigations.Furthermore,the suggested meshless method was found to be stable and accurate,demonstrating that it may be a viable alternative for solving natural heat transfer equations of nanofluids in enclosures with irregular geometries.

Dynamical Analysis of the Stochastic COVID-19 Model Using Piecewise Differential Equation Technique

Various data sets showing the prevalence of numerous viral diseases have demonstrated that the transmission is not truly homogeneous.Two examples are the spread of Spanish flu and COVID-19.The aimof this research is to develop a comprehensive nonlinear stochastic model having six cohorts relying on ordinary differential equations via piecewise fractional differential operators.Firstly,the strength number of the deterministic case is carried out.Then,for the stochastic model,we show that there is a critical number RS0 that can predict virus persistence and infection eradication.Because of the peculiarity of this notion,an interesting way to ensure the existence and uniqueness of the global positive solution characterized by the stochastic COVID-19 model is established by creating a sequence of appropriate Lyapunov candidates.Adetailed ergodic stationary distribution for the stochastic COVID-19 model is provided.Our findings demonstrate a piecewise numerical technique to generate simulation studies for these frameworks.The collected outcomes leave no doubt that this conception is a revolutionary doorway that will assist mankind in good perspective nature.

ESSENTIAL NORMS OF PRODUCTS OF WEIGHTED COMPOSITION OPERATORS AND DIFFERENTIATION OPERATORS BETWEEN BANACH SPACES OF ANALYTIC FUNCTIONS

We obtain several estimates of the essential norms of the products of differen- tiation operators and weighted composition operators between weighted Banach spaces of analytic functions with general weights. As applications, we also give estimates of the es- sential norms of weighted composition operators between weighted Banach space of analytic functions and Bloch-type spaces.

Shape Effect of Nanoparticles on Nanofluid Flow Containing Gyrotactic Microorganisms

In this paper,we discussed the effect of nanoparticles shape on bioconvection nanofluid flow over the vertical cone in a permeable medium.The nanofluid contains water,Al2O3 nanoparticles with sphere(spherical)and lamina(non-spherical)shapes and motile microorganisms.The phenomena of heat absorption/generation,Joule heating and thermal radiation with chemical reactions have been incorporated.The similarity transformations technique is used to transform a governing system of partial differential equations into ordinary differential equations.The numerical bvp4c MATLAB program is used to find the solution of ordinary differential equations.The interesting aspects of pertinent parameters on mass transfer,energy,concentration,and density of themotilemicroorganisms’profiles are computed and discussed.Our analysis depicts that the performance of sphere shape nanoparticles in the form of velocity distribution,temperature distribution,skin friction,Sherwood number and Motile density number is better than lamina(non-spherical)shapes nanoparticles.

Influences of double diffusion upon radiative flow of thin film Maxwell fluid through a stretching channel

This work explores the influence of double diffusion over thermally radiative flow of thin film hybrid nanofluid and irreversibility generation through a stretching channel.The nanoparticles of silver and alumina have mixed in the Maxwell fluid(base fluid).Magnetic field influence has been employed to channel in normal direction.Equations that are going to administer the fluid flow have been converted to dimension-free notations by using appropriate variables.Homotopy analysis method is used for the solution of the resultant equations.In this investigation it has pointed out that motion of fluid has declined with growth in magnetic effects,thin film thickness,and unsteadiness factor.Temperature of fluid has grown up with upsurge in Brownian motion,radiation factor,and thermophoresis effects,while it has declined with greater values of thermal Maxwell factor and thickness factor of the thin film.Concentration distribution has grown up with higher values of thermophoresis effects and has declined for augmentation in Brownian motion.

Modifications of the Optimal Auxiliary Function Method to Fractional Order Fornberg-Whitham Equations

In this paper,we present a new modification of the newly developed semi-analytical method named the Optimal Auxilary Function Method(OAFM)for fractional-order equations using the Caputo operator,which is named FOAFM.The mathematical theory of FOAFM is presented and the effectiveness of this method is proven by using it with well-known Fornberg-Whitham Equations(FWE).The FOAFM results are compared with other method results along with their exact solutions with the help of tables and plots to prove the validity of FOAFM.A rapidly convergent series solution is obtained from FOAFMand is validated by comparison with other results.The analysis proves that ourmethod is simply applicable,contains less computationalwork,and is rapidly convergent to the exact solution at the first iteration.A series solution to the problem is obtained with the help of FOAFM.The validity of FOAFM results is validated by comparing its results with the results available in the literature.It is observed that FOAFM is simply applicable,contains less computational work,and is fastly convergent.The convergence and stability are obtained with the help of optimal constants.FOAFM is very easy in applicability and provides excellent results at the first iteration for complex nonlinear initial/boundary value problems.FOAFM contains the optimal auxiliary constants through which we can control the convergence as FOAFM contains the auxiliary functions D_(1),D_(2),D_(3)...in which the optimal constants G_(1),G_(2),...and the control convergence parameters exist to play an important role in getting the convergent solution which is obtained rigorously.The computational work in FOAFM is less when compared to other methods and even a low-specification computer can do the computational work easily.

PRODUCTS OF WEIGHTED COMPOSITION AND DIFFERENTIATION OPERATORS INTO WEIGHTED ZYGMUND AND BLOCH SPACES

We characterize boundedness and compactness of products of differentiation op- erators and weighted composition operators between weighted Banach spaces of analytic functions and weighted Zygmund spaces or weighted Bloch spaces with general weights.

Comparative Analysis of COVID-19 Detection Methods Based on Neural Network

In 2019,the novel coronavirus disease 2019(COVID-19)ravaged the world.As of July 2021,there are about 192 million infected people worldwide and 4.1365 million deaths.At present,the new coronavirus is still spreading and circulating in many places around the world,especially since the emergence of Delta variant strains has increased the risk of the COVID-19 pandemic again.The symptoms of COVID-19 are diverse,and most patients have mild symptoms,with fever,dry cough,and fatigue as the main manifestations,and about 15.7%to 32.0%of patients will develop severe symptoms.Patients are screened in hospitals or primary care clinics as the initial step in the therapy for COVID-19.Although transcription-polymerase chain reaction(PCR)tests are still the primary method for making the final diagnosis,in hospitals today,the election protocol is based on medical imaging because it is quick and easy to use,which enables doctors to diagnose illnesses and their effects more quickly3.According to this approach,individuals who are thought to have COVID-19 first undergo an X-ray session and then,if further information is required,a CT-scan session.This methodology has led to a significant increase in the use of computed tomography scans(CT scans)and X-ray pictures in the clinic as substitute diagnostic methods for identifying COVID-19.To provide a significant collection of various datasets and methods used to diagnose COVID-19,this paper provides a comparative study of various state-of-the-art methods.The impact of medical imaging techniques on COVID-19 is also discussed.

Softζ-Rough Set and Its Applications in Decision Making of Coronavirus

In this paper,we present a proposed method for generating a soft rough approximation as a modification and generalization of Zhaowen et al.approach.Comparisons were obtained between our approach and the previous study and also.Eventually,an application on Coronavirus(COVID-19)has been presented,illustrated using our proposed concept,and some influencing results for symptoms of Coronavirus patients have been deduced.Moreover,following these concepts,we construct an algorithm and apply it to a decision-making problem to demonstrate the applicability of our proposed approach.Finally,a proposed approach that competes with others has been obtained,as well as realistic results for patients with Coronavirus.Moreover,we used MATLAB programming to obtain the results;these results are consistent with those of theWorld Health Organization and an accurate proposal competing with the method of Zhaowen et al.has been studied.Therefore,it is recommended that our proposed concept be used in future decision making.

New Trends in the Modeling of Diseases Through Computational Techniques

The computational techniques are a set of novel problem-solving methodologies that have attracted wider attention for their excellent performance.The handling strategies of real-world problems are artificial neural networks(ANN),evolutionary computing(EC),and many more.An estimated fifty thousand to ninety thousand new leishmaniasis cases occur annually,with only 25%to 45%reported to the World Health Organization(WHO).It remains one of the top parasitic diseases with outbreak and mortality potential.In 2020,more than ninety percent of new cases reported to World Health Organization(WHO)occurred in ten countries:Brazil,China,Ethiopia,Eritrea,India,Kenya,Somalia,South Sudan,Sudan,and Yemen.The transmission of visceral leishmaniasis is studied dynamically and numerically.The study included positivity,boundedness,equilibria,reproduction number,and local stability of the model in the dynamical analysis.Some detailed methods like Runge Kutta and Euler depend on time steps and violate the physical relevance of the disease.They produce negative and unbounded results,so in disease dynamics,such developments have no biological significance;in other words,these results are meaningless.But the implicit nonstandard finite difference method does not depend on time step,positive,bounded,dynamic and consistent.All the computational techniques and their results were compared using computer simulations.

Model of Fractional Heat Conduction in a Thermoelastic Thin Slim Strip under Thermal Shock and Temperature-Dependent Thermal Conductivity

The present paper paper,we estimate the theory of thermoelasticity a thin slim strip under the variable thermal conductivity in the fractional-order form is solved.Thermal stress theory considering the equation of heat conduction based on the time-fractional derivative of Caputo of order
is applied to obtain a solution.We assumed that the strip surface is to be free from traction and impacted by a thermal shock.The transform of Laplace(LT)and numerical inversion techniques of Laplace were considered for solving the governing basic equations.The inverse of the LT was applied in a numerical manner considering the Fourier expansion technique.The numerical results for the physical variables were calculated numerically and displayed via graphs.The parameter of fractional order effect and variation of thermal conductivity on the displacement,stress,and temperature were investigated and compared with the results of previous studies.The results indicated the strong effect of the external parameters,especially the timefractional derivative parameter on a thermoelastic thin slim strip phenomenon.

Generalization of Inequalities in Metric Spaces with Applications

In this paper, which serves as a continuation of earlier work, we generalize the idea of inequalities in metric spaces and use them to demonstrate that the incomplete metric space can be used to obtain a Banach space.

Approximate solutions for the problem of liquid film flow over an unsteady stretching sheet with thermal radiation and magnetic field

The proposed method is based on replacement of the unknown function by a truncated series of the shifted Legendre polynomial expansion. An approximate formula of the integer derivative is introduced. Special attention is given to study the convergence analysis and derive an upper bound of the error for the presented approximate formula. The introduced method converts the proposed equation by means of collocation points to a system of algebraic equations with shifted Legendre coefficients. Thus, after solving this system of equations, the shifted Legendre coefficients are obtained. This efficient numerical method is used to solve the system of ordinary differential equations which describe the thin film flow and heat transfer with the effects of the thermal radiation, magnetic field, and slip velocity.

Some Identities of the Degenerate Poly-Cauchy and Unipoly Cauchy Polynomials of the Second Kind

In this paper,we introduce modified degenerate polyexponential Cauchy(or poly-Cauchy)polynomials and numbers of the second kind and investigate some identities of these polynomials.We derive recurrence relations and the relationship between special polynomials and numbers.Also,we introduce modified degenerate unipolyCauchy polynomials of the second kind and derive some fruitful properties of these polynomials.In addition,positive associated beautiful zeros and graphical representations are displayed with the help of Mathematica.