Optimizing on a Global Scale with Random Search | Chapter 4 | Mathematics and Computer Science: Contemporary Developments Vol. 6

The challenge of identifying the global optimum in a space containing numerous local optima is a fundamental problem encountered by all systems capable of adapting and learning. GA offers a thorough search process for optimization.

 

Genetic Algorithms (GA) can be used to solve optimization issues, whether they are continuous or discrete in nature. This study uses binary coded GA approaches to function optimization, utilizing a variable length representation scheme and updated genetic operators.

 

Genes and chromosomes constitute the fundamental components of the binary genetic algorithm. The traditional binary genetic algorithm encodes optimization parameters into binary code strings. A gene in GA is represented as a binary digit. To create a population of individuals that represent search space points using the evolution model, the search process iteratively transforms a population of mathematical objects (typically fixed-length binary character strings) with fitness values into a new population of offspring objects. This is accomplished through the application of Darwinian natural selection and operations that are patterned after natural genetic operations such as crossover and mutation. Each individual is evaluated using an objective function for fitness. Consequently, generational evolution is inclined to yield fitter individuals and enhanced solutions within the search space. This process continues until the problem is resolved or no further improvements are observed.

 

Author (s) Details

Halah Ahmad Abd Almeneem Mhamd
Department of Mathematics, Darb University College, Jazan University, Jazan, 45142, Saudi Arabia.

 

Please see the book here:- https://doi.org/10.9734/bpi/mcscd/v6/2573

 

Gestational Care an Opportunity to Prevent NCDs in Future Generations| Chapter 3 | Perspective of Recent Advances in Medical Research Vol. 3

 In the case of diabetes, the intrauterine atmosphere significantly contributes to corpulence and diabetes epi­demics. The population accompanying an increased prevalence of diabetes will steadily be disproportionately troubled by the epidemics, which leads to a enduring broadening of health differences among racial and cultural groups. Understanding the transgenerational epidemiology and plant structure of diabetes is essential; developing simple, economical, and efficient stop strategies is vital. Performing up-to-date screening of meaningful women for glucose bigotry, attaining euglycemia, and ratifying appropriate nutrition n may counter all of the probabilities (i.e., the endless loop of transmission of glucose bigotry from one production to another). It is required to “Focus on the Fetus for the Future” to contain the epidemic of diabetes. To prevent noncommunicable ailments, GDM provides a meaningful opportunity for developing, experiment, and implementing dispassionate strategies.

Author(s) Details:

Rajesh Jain,
Community Medicine, Rama Medical College Hospital & Research Centre, Kanpur, India.

Anju Gahlot,
Community Medicine, Rama Medical College Hospital & Research Centre, Kanpur, India.

Chitra Rani Chauhan,
Community Medicine, Rama Medical College Hospital & Research Centre, Kanpur, India.

N. Bhavatharini,
SRC Diabetes Centre, Erode, Tamil Nadu, India.

V Seshiah,
Hony Distinguished Professor of The Tamil Nadu Dr. M.G.R Medical University, Tamil Nadu, India.

Please see the link here: https://stm.bookpi.org/PRAMR-V3/article/view/9061

A Descriptive Model of Amsams and Genes Transmission from Seven Generations | Chapter 12 | New Visions in Biological Science Vol. 2

 According to an article in the Tamil magazine Subayogam, during his reproductive years, a man will have 84 "amsams," 28 of his own and 56 passed down from his paternal line forefathers over six generations. The goal of the study was to compare the amsams passed down not only from paternal forefathers but also from maternal forefathers to the genes in the human genome. The authors of the current study concluded that the same 84 amsams found in men could also be found in the gametes of women, and that offspring receive amsams from both paternal and maternal grandmothers. The relationship between amsams and genes identified in Homo sapiens has also been studied. The individual's 28 amsams could be more or less equal to the non-identical 30 genes computed as 0.1 percent of 30,000 genes. The genetic constitution of the cloned cells differs from that of their parent, as evidenced by the amsams or genes.

Author (S) Details

Sayee Rajangam
Department of Anatomy, St. John’s Medical College, Bangalore 560 034, Karnataka, India.

N. Leelavathy
Ramaiah University of Applied Sciences, Karnataka, India.

View Book:- https://stm.bookpi.org/NVBS-V2/article/view/3718