# 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

200

Publications

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2,306

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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 (200)

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...

The research here was motivated by a number of recent studies on Hankel inequalities and sharp bounds. In this article, we define a new subclass of holomorphic convex functions that are related to tangent functions. We then derive geometric properties like the necessary and sufficient conditions, radius of convexity, growth, and distortion estimate...

In the context of multi-criteria group decision-making (MCGDM), the process involves categorizing criteria into distinct groups based on their inherent characteristics through a partitioning method. This research aims to create the partitioned Hamy mean (PHM) and the partitioned dual Hamy mean (PDHM) operators in the q\documentclass[12pt]{minimal}...

Considering the advantages of q-rung orthopair fuzzy 2-tuple linguistic set (q-RFLS), which includes both linguistic and numeric data to describe evaluations, this article aims to design a new decision-making methodology by integrating Vlsekriterijumska Optimizacija I Kompromisno Resenje (VIKOR) and qualitative flexible (QUALIFLEX) methods based on...

We introduce a class of analytic functions subordinated to \(1+\sinh \left( z\right)\) and obtain various necessary and sufficient conditions for functions to be in this class. These conditions mainly comprise of various results involving convolution. Further, we have obtained sharp five initial coefficients, a conjecture for the general nth coeffi...

Due to the fuzziness of the medical field, q-rung orthopair fuzzy 2-tuple linguistic (q-RF2L) set is the privileged way to aid medical professionals in conveying their assessments in the patient prioritization problem. The theme of the present study is to put forward a novel approach centered around the merging of prioritized averaging (PA) and the...

In recent years, the proliferation of Massive Open Online Courses (MOOC) platforms on a global scale has been remarkable. Learners can now meet their learning demands with the help of MOOC. However, learners might not understand the course material well if they have access to a lot of information due to their inadequate expertise and cognitive abil...

In this study, we define new class of holomorphic functions associated with tangent function. Furthermore, we examine the differential subordination implementation results related to Janowski and tangent functions. Also, we investigate some extreme point theorem and partial sums results, necessary and sufficient conditions, convex combination, clos...

The applications of rapidly advancing intelligent systems are so varied that many are still yet to be discovered. There is often a disconnect between experts in computer science, artificial intelligence, machine learning, robotics, and other specialties, which inhibits the potential for the expansion of this technology and its many benefits. A reso...

The notion of the “complex dual hesitant fuzzy set (CDHFS)” is the combination of the “dual hesitant fuzzy set (DHFS)” and the “complex fuzzy set (CFS).” It is characterized by two degrees, namely the membership and nonmembership, in the form of a finite subset on a unit disc in the complex plane. CDHFS is useful for dealing with real-world problem...

Machine Learning (ML) is an advanced technology that empowers systems to acquire knowledge autonomously, eliminating the need for explicit programming. The fundamental objective of the machine learning paradigm is to equip computers with the ability to learn independently without human intervention. In the literature, categorization in data mining...

Arabic is the language in which the Holy Quran was revealed to Mohammed (S.A.W). Muslims claim that the Holy Quran has not been tampered with since it has been preserved. The Arabic Quran should be read exactly as it has been written. With the flourishment of Islam and the appearance of faults in Quran’s recitation, the experts created Tajweed to p...

Smart strategies and intelligent technologies are enabling the designing of a smart learning environment that successfully supports the development of personalized learning and adaptive learning. This trend towards integration is in line with the growing prevalence of Internet of Things (IoT)-enabled smart education systems, which can leverage Mach...

The work presented in this article has been motivated by the recent research going on the Hankel determinant bounds and their related consequences, as well as the techniques used previously by many different authors. We aim to establish a new subfamily of holomorphic functions connected with the hyperbolic tangent function with bounded boundary rot...

Molecular topology can be described by using topological indices. These are quantitative measures
of the essential structural features of a proposed molecule calculated from its molecular structure.
It is a numerical value obtained from a molecular configuration that reflects the significant
physical characteristics of the suggested molecule. Numer...

Learning activities are considerably supported and improved by the rapid advancement of e-learning systems. This gives students a tremendous chance to participate in learning activities worldwide. The Massive Open Online Courses (MOOCs) platform has emerged as one of the most significant platforms for e-learning as a result of the rapid growth of n...

In the present article, we define and investigate a new subfamily of holomorphic functions connected with the cosine hyperbolic function with bounded turning. Further some interesting results like sharp coefficients bounds, sharp Fekete-Szegö estimate, sharp $ 2^{nd} $ Hankel determinant and non-sharp $ 3^{rd} $ order Hankel determinant. Moreover,...

Intuitionistic fuzzy sets (IFSs) are key concepts in ambiguity and uncertainty. However, IFSs deal only with anticipation, not periodicity. To do so, complex intuitionistic fuzzy sets (CIFS) can handle uncertainties and periodicity simultaneously. Also, the Maclaurin symmetric mean (MSM) operator is a better tool for dealing with the criteria’s int...

Feature selection in high dimensional gene expression datasets not only reduces the dimension of the data, but also the execution time and computational cost of the underlying classifier. The current study introduces a novel feature selection method called weighted signal to noise ratio (WSNR) by exploiting the weights of features based on support...

This paper proposes two novel approaches based on feature weighting and model selection for building more accurate kNN ensembles. The first approach identifies the nearest observations using a feature weighting scheme concerning the response variable via support vectors. A randomly selected subset of features is used for the feature weighting and m...

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...

In medicine, "imaging" refers to the technique or technology of seeing in or out of a living organism to discern the constituent parts of that body. During the operation, the medical diagnosis is examined, an analysis of the disease is performed, and image data sets that are considered normal and abnormal are created. Two different types of images...

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 ma...

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 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...

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...

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 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...