
Wali Khan MashwaniKohat University of Science and Technology | kust · Department of Mathematics
Wali Khan Mashwani
PhD in Mathematics (University of Essex UK)
Looking for Research Collaboration with active Researchers.
About
171
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1,459
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Introduction
Presently, I am working as a Professor of Mathematics, Dean Faculty of Physical and Numerical Science at KUST. My main interest lies in developing faster and more efficient evolutionary algorithms for single and multi-objective optimization problems, Machine Learning Approaches and Artificial Neural Networks, modeling and analyzing different mathematical and statistical models, and Complex Analysis. For more information, please visit: https://kust.edu.pk/kust/index.php/insf/376-director
Additional affiliations
July 2012 - July 2016
September 2008 - January 2012
February 2008 - January 2012
Education
June 2005 - June 2007
January 1994 - August 1996
January 1992 - August 1994
Publications
Publications (171)
In recent years, hybridization of multi-objective evolutionary algorithms (MOEAs) with traditional mathematical programming techniques have received significant attention in the field of evolutionary computing (EC). The use of multiple strategies with self-adaptation manners can further improve the algorithmic performances of decomposition-based ev...
Different crossover operators suit different problems. It is, therefore, potentially problematic to chose the ideal crossover operator in an evolutionary optimization scheme. Using multiple crossover operators could be an effective way to address this issue. This paper reports on the implementation of this idea, i.e. the use of two crossover operat...
Different genetic operators suit different problems. Using several crossover operators should be an effective approach for improving the performance of an evolutionary algorithm. This paper studies the effect of the use of two crossover operators on MOEA/D-DRA for multi-objective optimization. It considers two crossover operators, namely, simplex c...
Integration of single methods into hybrid are researched scarcely in the recent past. This paper investigates the effect of integration of single methods: MOEA/D and NSGA-II in a multimethod search approach, so-called, MMTD, based on self-adaptive generations level proposed in this paper. During implementation, MMTD borrows some concepts from the s...
Integration of single methods into their hybrids are researched scarcely in the recent few years. This paper presents the feasibility study for integration of two methods: MOEA/D [7] and NSGA-II [4] in the proposed multimethod search approach (MMTD). During implementation of MMTD, we borrows some concepts from the specialized literature of EMO. In...
q-ROPFLS, including numeric and linguistic data, has a wide range of applications in handling uncertain information. This article aims to investigate q-ROPFL correlation coefficient based on the proposed information energy and covariance formulas. Moreover, considering that different q-ROPFL elements may have varying criteria weights, the weighted...
In this article, we define the class of bounded turning functions connected with three leaf function to investigate results for the estimates of four initial coefficients, Fekete-Szegö functional, the second-order Hankel determinant and Zalcman conjecture and these results are shown to be sharp. Furthermore, we estimate the bounds of the third-orde...
This study describes the construction of a new algorithm where image processing along with the two-step quasi-Newton methods is used in biomedical image analysis. It is a well-known fact that medical informatics is an essential component in the perspective of health care. Image processing and imaging technology are the recent advances in medical in...
The rough set (RS) theory is a successful approach for studying the uncertainty in data. In contrast, the bipolar soft sets (BSS) can deal with the uncertainty, as well as bipolarity of the data in many situations. In 2018, Karaaslan and Cagman proposed bipolar soft rough sets (BSRSs), a hybridization of RS and BSS. However, certain shortcomings wi...
A topological index is a number derived from a molecular structure (i.e., a graph) that represents the fundamental structural characteristics of a suggested molecule. Various topological indices, including the atom-bond connectivity index, the geometric–arithmetic index, and the Randic index, can be utilized to determine various characteristics, su...
The aim of this article is to save the energy consumption and tasks’ completion time of multi-unmanned aerial vehicle (UAV) by jointly optimizing the trajectories of UAVs and passive phase shifts of intelligent reflecting surface (IRS)s. By applying this approach, the system will lead to complex optimization problem as it has several optimization s...
The rough set (RS) theory is a successful approach for studying the uncertainty in data. In contrast, the bipolar soft sets (BSS) can deal with the uncertainty, as well as bipolarity of the data in many situations. In 2018, Karaaslan and Ç agman [39] proposed bipolar soft rough sets (BSRSs), a hybridization of RS and BSS. However, certain shortcomi...
Linguistic Pythagorean fuzzy numbers (LPFNs) are better tools for dealing with imprecision and vagueness. This article develops a new multi-attribute group decision-making approach with LPFNs. The attribute values are LPFNs, and the information about the attribute weight is incomplete. Extended the notion of the traditional GRA method, a new extens...
This paper presents a multi-unmanned aerial vehicle (UAV)-assisted mobile edge computing system, where multiple UAVs are used to serve mobile users. We aim to minimize the overall energy consumption of the system by planning the trajectories of UAVs. To plan the trajectories of UAVs, we need to consider the deployment of hovering points (HPs) of UA...
To solve constrained optimization problems (COPs), teaching learning-based optimization (TLBO) has been used in this study as a baseline algorithm. Different constraint handling techniques (CHTs) are incorporated in the framework of TLBO. The superiority of feasibility (SF) is one of the most commonly used and much effective CHTs with various decis...
Large-scale global optimization problems are ambitious and quite difficult to handle with deterministic methods. The use of stochastic optimization techniques is a good choice for dealing with these problems. Nature-inspired algorithms (NIAs) are stochastic in nature, computer-based, and quite easy to implement due to their population-based nature....
Novel Pandemic COVID-19 led globally to severe health barriers and financial issues in different parts of the world. The forecast on COVID-19 infections is significant. Demeanor vital data will help in executing policies to reduce the number of cases efficiently. Filtering techniques are appropriate for dynamic model structures as it provide reason...
In recent years, using the idea of analytic and bi-univalent functions , many ideas have been developed by different well-known authors, but the using Gegenbauer polynomials along with certain bi-univalent functions is very rare in the literature. We are essentially motivated by this recent research going on, here in our present investigation , we...
Teaching learning-based optimization is one of the widely accepted metaheuristic algorithms inspired by teaching and learning within classrooms. It has successfully addressed several real-world optimization problems, but it may still be trapped in local optima and may suffer from the problem of premature convergence in the case of solving some chal...
Phenomena such as black hole (BH) growth, Hawking radiation and gravitational waves are captivating not only in changing spacetime's curvature but also in affecting the thermodynamics characteristics of the sources with respect to time. The current study aims at exploring the effects of time and quintessential dark energy on the thermodynamical pro...
The Coronavirus disease (COVID-19) most likely began in an animal species and subsequently transmitted to humans in Wuhan, China, a city of 11 million people, on December 29, 2019, when the first case was recorded. The Coronavirus then transmitted from person to person by infected droplets from a sick person's coughing, sneezing, or contaminated ha...
In this study, we first propose a new general family of distributions which both unify a
a plethora of well-established lifetime distributions and offer new perspectives of work. Then, we focus on a special member of the family by taking the so-called modified Weibull distribution as a baseline, standing out from the competition for having a very f...
The present study introduces a q-rung orthopair hesitant fuzzy stochastic method based on regret theory to capture the psychological behavior of decision makers (DMs) in decision making. For this, first, according to the score and variance function of q-rung orthopair hesitant fuzzy number (q-ROHFN), a novel group satisfaction degree is defined, wh...
This paper presents an energy and task completion time minimization scheme for the unmanned aerial vehicles (UAVs)-empowered mobile edge computing (MEC) system, where several UAVs are deployed to serve large-scale users’ equipment (UEs). The aim is to minimize the weighted sum of energy consumption and task completion time of the system by planning...
Keeping in view the latest trends toward quantum calculus, due to its various applications in physics and applied mathematics, we introduce a new subclass of meromorphic multivalent functions in Janowski domain with the help of the q-differential operator. Furthermore, we investigate some useful geometric and algebraic properties of these functions...
In this article, a new lifetime model, referred to as modified Frechet–Rayleigh distribution (MFRD), is developed by accommodating an additional parameter in Rayleigh distribution on the basis of the modified Frechet method. Numerous statistical properties of the suggested model are derived and discussed. The technique of maximum likelihood (ML) es...
In this paper, a new generalization of the Generalized Pareto distribution is proposed using the generator suggested in [1], named as Khalil Extended Generalized Pareto (KEGP) distribution. Various shapes of the suggested model and important mathematical properties are investigated that includes moments, quantile function, moment-generating functio...
In this article, Burr III distribution is proposed with a significantly improved functional
form. This new modification has enhanced the flexibility of the classical distribution with the
ability to model all shapes of hazard rate function including increasing, decreasing, bathtub, upsidedown
bathtub, and nearly constant. Some of its elementary pro...
In our present investigation, we obtain the improved third-order Hankel determinant for a class of starlike functions connected with modified sigmoid functions. Further, we investigate the fourth-order Hankel determinant, Zalcman conjecture, and also evaluate the fourth-order Hankel determinants for 2-fold, 3-fold, and 4-fold symmetric starlike fun...
In this article, Burr III distribution is proposed with a significantly improved functional form. This new modification has enhanced the flexibility of the classical distribution with the ability to model all shapes of hazard rate function including increasing, decreasing, bathtub, upside-down bathtub, and nearly constant. Some of its elementary pr...
The estimation of the fuzzy membership function parameters for interval type 2 fuzzy logic system (IT2-FLS) is a challenging task in the presence of uncertainty and imprecision. Grasshopper optimization algorithm (GOA) is a fresh population-based meta-heuristic algorithm that mimics the swarming behavior of grasshoppers in nature, which has good co...
The 3D Prandtl fluid flow through a bidirectional extending surface is analytically investigated. Cattaneo–Christov fluid model is employed to govern the heat and mass flux during fluid motion. The Prandtl fluid motion is mathematically modeled using the law of conservations of mass, momentum, and energy. The set of coupled nonlinear PDEs is conver...
Nowadays, the whole world is facing a pandemic situation in the form of coronavirus diseases (COVID-19). In connection with the spread of COVID-19 confirmed cases and deaths, various researchers have analysed the impact of temperature and humidity on the spread of coronavirus. In this paper, a deep transfer learning-based exhaustive analysis is per...
The main objective of the present article is to define the class of bounded turning functions associated with modified sigmoid function. Also we investigate and determine sharp results for the estimates of four initial coefficients, Fekete-Szegö functional, the second-order Hankel determinant, Zalcman conjucture and Krushkal inequality. Furthermore...
In this article, we introduce a new class of multivalent analytic functions associated with petal-shape region. Furthermore, some useful properties, such as the Fekete–Szegö inequality, and their consequences for some special cases are discussed. For some specific value of function f, we obtain sufficient conditions for multivalent starlike functio...
In this manuscript, we investigate the estimation of the unknown reliability measure R = P [Y < X], in the case where Y and X are two independent random variables with Topp–Leone distributions. As the main contribution, various advanced sampling strategies are studied. The suggested strategies are simple random, ranked set, and median ranked set sa...
Symmetry methods for differential equations are a powerful tool for the solutions of differential equations. It linearizes nonlinear differential equations, reduces the order of differential equations, reduces the number of independent variables in partial differential equations, and solves almost all those differential equations for which the othe...
In this study, the boundary layer phenomena for stagnation point flow of water-based nanofluids is being observed with the upshot of MHD and convective heating on a nonlinear stretching surface. To develop a fundamental flow model, a boundary layer approximation is done, which signifies time-dependent momentum, energy, and concentration expressions...
By making use of the concept of basic (or q-) calculus, many subclasses of analytic and symmetric q-starlike functions have been defined and studied from different viewpoints and perspectives. In this article, we introduce a new class of meromorphic multivalent close-to-convex functions with the help of a q-differential operator. Furthermore, we in...
In our present investigation, some coefficient functionals for a subclass relating to starlike functions connected with three-leaf mappings were considered. Sharp coefficient estimates for the first four initial coefficients of the functions of this class are addressed. Furthermore, we obtain the Fekete–Szegö inequality, sharp upper bounds for seco...
This paper presents a multi-unmanned aerial vehicle (UAV)-assisted mobile edge computing (MEC) system, where multiple UAVs (variable number of UAVs) are deployed to serve Internet of Things devices (IoTDs). We aim to minimize the sum of hovering and flying energies of UAVs by optimizing the trajectories of UAVs. The problem is very complicated as w...
In this paper, a new approach for deriving continuous probability distributions is developed by incorporating an extra parameter to the existing distributions. Frechet distribution is used as a submodel for an illustration to have a new continuous probability model, termed as modified Frechet (MF) distribution. Several important statistical propert...
Teaching learning based optimization (TLBO) is a stochastic algorithm which was first proposed for unconstrained optimization problems. It is population based, nature-inspired, and meta-heuristic that imitates teaching learning process. It has two phases, teacher and learner. In teacher phase, the teacher who is well-learned person transfers his/he...
Keeping in view the various important applications of Mittag-Leffer functions in the fields of applied sciences, we introduce Pascu-type analytic functions utilizing the concept of Mittag-Leffler functions in the region of Janowski domain. Moreover, we investigate some useful properties of these functions such as sufficiency criteria, distortion an...
COVID-19 is a virus that spreads globally, causing severe health complications and substantial economic impact in various parts of the world. The COVID-19 forecast on infections is significant and crucial information that will help in executing policies and effectively reducing the daily cases. Filtering techniques are important ways to model dynam...
Abstract. In this paper we elaborated the concept that on what conditions left almost semigroup (LA-Semigroup), right almost semigroup
(RA-Semigroup) and a groupoid become commutative and further extended these results on medial, LA-Group and RA-Group. We proved
that the relation of LA-Semigroup with left double displacement semigroup (LDD-semigrou...
In this article, we introduce a new subclass of analytic functions utilizing the idea of Mittag-Leffler type Poisson distribution associated with the Janowski functions. Further, we discuss some important geometric properties like necessary and sufficient condition, convex combination, growth and distortion bounds, Fekete-Szegö inequality, and part...
In this article, the ideas of post-quantum calculus and meromorphic multivalent functions are combined and some applications of these functions are discussed. We introduce a new subclass of meromorphic multivalent functions in association with Janowski domain. We investigate and study some useful geometric properties of this class of functions such...
In this article, by utilizing the theory of quantum (or q-) calculus, we define a new subclass of analytic and multivalent (or p-valent) functions class Ap, where class Ap is invariant (or symmetric) under rotations. The well-known class of Janowski functions are used with the help of the principle of subordination between analytic functions in ord...
The hydrodynamic flow of an incompressible and isotropic Casson fluid through a yawed cylinder is investigated by employing continuity, momentum, and energy equations satisfying suitable boundary conditions. The density variation is governed by Boussinesq approximation. The model equations consisting of coupled partial differential equations (PDEs)...
The Korteweg–de Vries (KdV) equation is a weakly nonlinear third-order differential equation which models and governs the evolution of fixed wave structures. This paper presents the analysis of the approximate symmetries along with conservation laws corresponding to the perturbed KdV equation for different classes of the perturbed function. Partial...
Evolutionary computing is an exciting sub-field of soft computing. Many evolutionary algorithm based on the Darwinian principles of natural selection are developed under the umbrella of EC in the last two decades. EAs provide a set of optimal solutions in single simulation unlike traditional optimization techniques for dealing with large-scale glob...
The western Himalayan region in northern Pakistan is one of the most sensitive hotspots to climate change, due to the rapidly increasing population and delicate mountainous ecosystem. The relatively limited observed instrumental record impedes our understanding of long-term climate variability and their assessment. Using standard dendrochronologica...
Recent years have witnessed the use of metaheuristic algorithms to solve the optimization problems that usually require extensive computations and time. Among others, scatter search is the widely used evolutionary metaheuristic algorithm. It uses the information of global optima, which is stored in a different and unique set of solutions. In this p...
In this paper, a new method is proposed to expand the family of lifetime distributions. The suggested method is named as Khalil new generalized family (KNGF) of distributions. A special submodel, termed as Khalil new generalized Pareto (KNGP) distribution, is investigated from the family with one shape and two scale parameters. A number of mathemat...
Modern reliability engineering accelerated life tests (ALT) and partially accelerated life tests (PALT) are widely used to obtain the timely information on the reliability of objects, products, elements, and materials as well as to save time and cost. The ALTs or PALTs are useful in determining the failed manners of the items at routine conditions...
The 3D Carreau fluid flow through a porous and stretching (shrinking) sheet is examined analytically by taking into account the effects of mass transfer, thermal radiation, and Hall current. The model equations, which consist of coupled partial differential equations (PDEs), are simplified to ordinary differential equations (ODEs) through appropria...
This paper introduces new learning to the prediction model to enhance the prediction algorithms’ performance in dynamic circumstances. We have proposed a novel technique based on the alpha-beta filter and deep extreme learning machine (DELM) algorithm named as learning to alpha-beta filter. The proposed method has two main components, namely the pr...
The main aim of the present article is the introduction of a new differential operator in q-analogue for meromorphic multivalent functions which are analytic in punctured open unit disc. A subclass of meromorphic multivalent convex functions is defined using this new differential operator in q-analogue. Furthermore, we discuss a number of useful ge...
In this research article we consider two well known subclasses of starlike and bounded turning functions associated with nephroid domain. Our aims to find third Hankel determinant for these classes.
Model selection is an important and challenging problem in statistics. The model selection is inevitable in a large number of applications including life sciences, social sciences, business, or economics. In this article, we propose a resampling-based information criterion called paired bootstrap criterion (PBC) for model selection. The proposed cr...