Algorithm Analysis
Algorithm analysis involves evaluating the efficiency and performance of algorithms in terms of time and space complexity. It aims to understand how the algorithm's running time and resource usage scale with input size. This analysis helps in comparing different algorithms and selecting the most suitable one for a specific problem or application.
3 Key excerpts on "Algorithm Analysis"
eBook - ePubThe Cyber Patient
Navigating Virtual Informatics
- Rebecca Mendoza Saltiel Busch(Author)
- 2019(Publication Date)
- Productivity Press(Publisher)
...Chapter 6 Algorithms Effective algorithms make assumptions, show a bias toward a simple solution, trade off the costs of error against the cost of delay, and take chances. Brian Christian American nonfiction, science, and philosophy author Tom Griffiths Professor of Psychology and Cognitive Science at UC Berkeley and Director, Computational Cognitive Science Lab Introduction An algorithm is a constructed set of specifically defined procedures that act upon stored or input data in a specified sequence. An algorithm answers a specific question in response to a hypothesis or to generate intelligence to create a hypothesis for further analysis. The key is to ask the right question that will have a measurable impact on day-to-day health decisions. This chapter provides a fundamental overview of algorithms. These concepts have been applied among all technology platforms. Understanding Algorithms Algorithms can execute a process or build models for predictive behavioral analysis. An algorithm could be an informal set of processes or a formal, specifically defined process. Formal processes are required for algorithms managed via the use of a computer programming language that tells the computer what to do. One simple algorithm written for an insurance company’s claims adjudication system requires that, for every claim submitted, a patient be a member of the company’s insurance program. If the patient is not part of that program, then the algorithm directs the insurance company to deny the claim. An informal algorithm can be expressed using everyday language. Language coupled with the structure of grammar and use of known references can create a prescribed set of procedures. Consider the following narrative: At approximately 8 a.m. the students will arrive at school to register for the final examination. The test will begin at 9 a.m. Late arrivals will not be allowed into the examination room. The relationships in the narrative are straightforward...
eBook - ePub- David Beer, David Beer(Authors)
- 2019(Publication Date)
- Routledge(Publisher)
...With respect to the latter, the paper provides a critical appraisal of six methodological approaches that might profitably be used to produce insights into the nature and work of algorithms. Thinking critically about algorithms While an algorithm is commonly understood as a set of defined steps to produce particular outputs it is important to note that this is somewhat of a simplification. What constitutes an algorithm has changed over time and they can be thought about in a number of ways: technically, computationally, mathematically, politically, culturally, economically, contextually, materially, philosophically, ethically and so on. Miyazaki (2012) traces the term ‘algorithm’ to twelfth-century Spain when the scripts of the Arabian mathematician Muḥammad ibn Mūsā al-Khwārizmī were translated into Latin. These scripts describe methods of addition, subtraction, multiplication and division using numbers. Thereafter, ‘algorism’ meant ‘the specific step-by-step method of performing written elementary arithmetic’ (Miyazaki, 2012, p. 2) and ‘came to describe any method of systematic or automatic calculation’ (Steiner, 2012, p. 55). By the mid-twentieth century and the development of scientific computation and early high level programming languages, such as Algol 58 and its derivatives (short for ALGOrithmic Language), an algorithm was understood to be a set of defined steps that if followed in the correct order will computationally process input (instructions and/or data) to produce a desired outcome (Miyazaki, 2012). From a computational and programming perspective an ‘Algorithm = Logic + Control’; where the logic is the problem domain-specific component and specifies the abstract formulation and expression of a solution (what is to be done) and the control component is the problem-solving strategy and the instructions for processing the logic under different scenarios (how it should be done) (Kowalski, 1979)...
eBook - ePub- Xin-She Yang(Author)
- 2020(Publication Date)
- Academic Press(Publisher)
...Because resources, time, and money are always limited in real-world applications, we have to find solutions to optimally use these valuable resources under various constraints, ideally in a sustainable way. Mathematical optimization or programming is the study of such planning and design problems using mathematical tools. Since most real-world applications are often highly nonlinear, they require sophisticated optimization tools to tackle. Nowadays, computer simulations become an indispensable tool for solving such optimization problems with various efficient search algorithms.Behind any computer simulation and computational methods, there are always some algorithms at work. The basic components and the ways of they interact determine how an algorithm works and the efficiency and performance of the algorithm.This chapter introduces algorithms and analyze the essence of the algorithms. Then we discuss the general formulation of an optimization problem and describe the modern approaches in terms of swarm intelligence and bio-inspired computation. A brief history of nature-inspired algorithms is reviewed.1.1 What Is an Algorithm?In essence, analgorithmis a step-by-step procedure of providing calculations or instructions. Many algorithms are iterative. The actual steps and procedures depend on the algorithm used and the context of interest. However, in this book, we mainly concern ourselves with the algorithms for optimization, and thus we place more emphasis on iterative procedure for constructing algorithms.For example, a simple algorithm of finding the square root of any positive numberk>0orx, can be written asxt+1=12(xt+kxt),(1.1)starting from a guess solutionx0≠0, say,x0=1...
