menu
{ "item_title" : "Stochastic Analysis For Some Non-Linear Epidemic Models", "item_author" : [" Adel Settati", "Aadil Lahrouz", "Mourad El Idrissi "], "item_description" : "Stochastic calculus has emerged as a robust mathematical framework for modeling complex biological systems characterized by inherent randomness and uncertainty. Unlike traditional deterministic models, which often fail to capture the variability observed in biological processes, stochastic calculus allows for directly incorporating noise and random fluctuations into the modeling equations. This approach is efficient in areas such as population dynamics, gene expression, neural activity, and the spread of infectious diseases, where biological systems are influenced by numerous random factors at both the microscopic and macroscopic levels. By utilizing tools such as stochastic differential equations (SDEs) and the Itcalculus, researchers can describe the temporal evolution of biological systems in a manner that accounts for both the deterministic trends and stochastic perturbations.", "item_img_path" : "https://covers1.booksamillion.com/covers/bam/3/65/946/353/3659463531_b.jpg", "price_data" : { "retail_price" : "46.00", "online_price" : "46.00", "our_price" : "46.00", "club_price" : "46.00", "savings_pct" : "0", "savings_amt" : "0.00", "club_savings_pct" : "0", "club_savings_amt" : "0.00", "discount_pct" : "10", "store_price" : "" } }
Stochastic Analysis For Some Non-Linear Epidemic Models|Adel Settati

Stochastic Analysis For Some Non-Linear Epidemic Models

local_shippingShip to Me
In Stock.
FREE Shipping for Club Members help

Overview

Stochastic calculus has emerged as a robust mathematical framework for modeling complex biological systems characterized by inherent randomness and uncertainty. Unlike traditional deterministic models, which often fail to capture the variability observed in biological processes, stochastic calculus allows for directly incorporating noise and random fluctuations into the modeling equations. This approach is efficient in areas such as population dynamics, gene expression, neural activity, and the spread of infectious diseases, where biological systems are influenced by numerous random factors at both the microscopic and macroscopic levels. By utilizing tools such as stochastic differential equations (SDEs) and the It calculus, researchers can describe the temporal evolution of biological systems in a manner that accounts for both the deterministic trends and stochastic perturbations.

This item is Non-Returnable

Details

  • ISBN-13: 9783659463532
  • ISBN-10: 3659463531
  • Publisher: LAP Lambert Academic Publishing
  • Publish Date: October 2024
  • Dimensions: 9 x 6 x 0.19 inches
  • Shipping Weight: 0.28 pounds
  • Page Count: 80

Related Categories

You May Also Like...

    1

BAM Customer Reviews