Intelligent predictive stochastic computing for nonlinear differential delay computer virus model

Anwar, Nabeela; Ahmad, Iftikhar; Kiani, Adiqa Kausar; Naz, Shazia; Shoaib, Mohammed; Raja, Muhammad Asif Zahoor

doi:10.1080/17455030.2022.2155327

Cited by 8 publications

(2 citation statements)

References 63 publications

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“…Overall, the justifications for introducing new optimization algorithms include improved efficiency, handling complex problems, robustness, overcoming local optima, problem-specific optimization, and leveraging advancements in computing power. These justifications drive progress in optimization research, providing more effective solutions to real-world problems 13 – 15 .…”

Section: Introductionmentioning

confidence: 99%

Resistance–capacitance optimizer: a physics-inspired population-based algorithm for numerical and industrial engineering computation problems

Ravichandran,

Manoharan,

Jangir

et al. 2023

Sci Rep

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The primary objective of this study is to delve into the application and validation of the Resistance Capacitance Optimization Algorithm (RCOA)—a new, physics-inspired metaheuristic optimization algorithm. The RCOA, intriguingly inspired by the time response of a resistance–capacitance circuit to a sudden voltage fluctuation, has been earmarked for solving complex numerical and engineering design optimization problems. Uniquely, the RCOA operates without any control/tunable parameters. In the first phase of this study, we evaluated the RCOA's credibility and functionality by deploying it on a set of 23 benchmark test functions. This was followed by thoroughly examining its application in eight distinct constrained engineering design optimization scenarios. This methodical approach was undertaken to dissect and understand the algorithm's exploration and exploitation phases, leveraging standard benchmark functions as the yardstick. The principal findings underline the significant effectiveness of the RCOA, especially when contrasted against various state-of-the-art algorithms in the field. Beyond its apparent superiority, the RCOA was put through rigorous statistical non-parametric testing, further endorsing its reliability as an innovative tool for handling complex engineering design problems. The conclusion of this research underscores the RCOA's strong performance in terms of reliability and precision, particularly in tackling constrained engineering design optimization challenges. This statement, derived from the systematic study, strengthens RCOA's position as a potentially transformative tool in the mathematical optimization landscape. It also paves the way for further exploration and adaptation of physics-inspired algorithms in the broader realm of optimization problems.

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Section: Introductionmentioning

confidence: 99%

Resistance–capacitance optimizer: a physics-inspired population-based algorithm for numerical and industrial engineering computation problems

Ravichandran,

Manoharan,

Jangir

et al. 2023

Sci Rep

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“…Many researchers used a variety of numerical methods to simulate the solution of mathematical models, acquiring results that were more accurate than those found in the literature, such as [39][40][41][42][43]. Researchers have recently focused their efforts on the numerical solutions of numerous mathematical models in the realm of epidemiology, such as the HIV model [44], COVID-19 [45], plant disease model [46], tuberculosis propagation model [47], computer virus transmission model [48]. Although the above mentioned techniques have high precision and consistency but they require considerable memory and long computational cost.…”

Section: Introductionmentioning

confidence: 99%

Numerical treatment for mathematical model of farming awareness in crop pest management

Anwar,

Ahmad,

Kiani

et al. 2023

Front. Appl. Math. Stat.

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The most important factor for increasing crop production is pest and pathogen resistance, which has a major impact on global food security. Pest management also emphasizes the need for farming awareness. A high crop yield is ultimately achieved by protecting crops from pests and raising public awareness of the devastation caused by pests. In this research, we aim to investigate the intricate impacts of nonlinear delayed systems for managing crop pest management (CPM) supervised by Ordinary Differential Equations (ODEs). Our focus will be on highlighting the intricate and often unpredictable relationships that occur over time among crops, pests, strategies for rehabilitation, and environmental factors. The nonlinear delayed CPM model incorporated the four compartments: crop biomass density [B(t)], susceptible pest density [S(t)], infected pest density [I(t)], and population awareness level [A(t)]. The approximate solutions for the four compartments B(t), S(t), I(t), and A(t) are determined by the implementation of sundry scenarios generated with the variation in crop biomass growth rate, rate of pest attacks, pest natural death rate, disease associated death rate and memory loss of aware people, by means of exploiting the strength of the Adams (ADS) and explicit Runge-Kutta (ERK) numerical solvers. Comparative analysis of the designed approach is carried out for the dynamic impacts of the nonlinear delayed CPM model in terms of numerical outcomes and simulations based on sundry scenarios.

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On analysis of fractional order HIV infection model with the adaptive immune response under Caputo operator

Ahmad

Ali

et al. 2022

J. Appl. Math. Comput.

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Intelligent predictive stochastic computing for nonlinear differential delay computer virus model

Cited by 8 publications

References 63 publications

Resistance–capacitance optimizer: a physics-inspired population-based algorithm for numerical and industrial engineering computation problems

Resistance–capacitance optimizer: a physics-inspired population-based algorithm for numerical and industrial engineering computation problems

Numerical treatment for mathematical model of farming awareness in crop pest management

On analysis of fractional order HIV infection model with the adaptive immune response under Caputo operator

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