**Algorithm Design** News

Next step of safecoin algorithm design This post is about a possible safecoin algorithm that could be a next step in design following RFC-0004 Farm Attempt and RFC-0012 Safecoin Implementation (both from 2015). The main new idea it introduces is target para…

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Generative Design Algorithms Prepare For Space NASA is famously risk-averse, taking cautious approaches because billions of taxpayer dollars are at stake and each failure receives far more political attention than their many successes. So while

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Joint and Control Charts Optimal Design Using Genetic Algorithm A simple and flexible model for economic statistical design of joint and control charts was proposed. The design problem was approached by constrained fuzzy multiobjective modeling for three objectives: joint power, joint Type I error, and joint total control cost. Fuzzy membership functions were created to measure the satisfaction levels of the objectives, and the overall satisfaction level of the design was calculated using a weighted-average method. A genetic algorithm was designed to solve this model. The strength of this model lies in its effectiveness in detecting the assignable causes through the joint design and in its simplicity and flexibility in dealing with uncertainties in the design.

Summary: Algorithms to Live By My book summaries are designed as captures for what I've read, and aren't necessarily great standalone resources for those who have not read the book.

Artificial intelligence algorithm may predict Alzheimer's disease, five years in advance Artificial intelligence algorithm may predict Alzheimer's disease, five years in advance - Scientists -- including one of Indian origin -- have created an artificial intelligence (AI) algorithm that can accurately predict whether a person's cognitive decline will lead to Alzheimer's disease in the next five years.Researchers from the University of Toronto in Canada designed an algorithm that learns signatures from magnetic resonance imaging (MRI), genetics, and clinical data.

The wheels on the algorithm Sir, It seems that whoever designed the new proposed timetabling and routes for Dublins buses used a generic type of algorithm to generate a solution. Anyone with even a basic knowledge of timetabling would know that these simply come up with the least number of buses required to operate the largest number of routes, with no regard for what is actually required by the users the commuters. Would someone tell the consultants that these mathematical solutions might work for the likes of Seven Bridges of Knigsberg problem, but they are pretty much useless in the real world. Yours, etc, LIAM POWER, Dundalk, Co Louth.

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**Algorithm Design** Summary

Procedure for calculation

**Algorithm** also known as **mathematical algorithm**

In mathematics and computer science, an algorithm ( (listen)) is an unambiguous specification of how to solve a class of problems. Algorithms can perform calculation, data processing, and automated reasoning tasks.
As an effective method, an algorithm can be expressed within a finite amount of space and time and in a well-defined formal language for calculating a function. Starting from an initial state and initial input (perhaps empty), the instructions describe a computation that, when executed, proceeds through a finite number of well-defined successive states, eventually producing "output" and terminating at a final ending state. The transition from one state to the next is not necessarily deterministic; some algorithms, known as randomized algorithms, incorporate random input.The concept of algorithm has existed for centuries. Greek mathematicians used algorithms in, for example, the sieve of Eratosthenes for finding prime numbers and the Euclidean algorithm for finding the greatest common divisor of two numbers.The word algorithm itself derives from the 9th century mathematician Muḥammad ibn Mūsā al-Khwārizmī, Latinized Algoritmi. A partial formalization of what would become the modern concept of algorithm began with attempts to solve the Entscheidungsproblem (decision problem) posed by David Hilbert in 1928. Later formalizations were framed as attempts to define "effective calculability" or "effective method". Those formalizations included the Gödel–Herbrand–Kleene recursive functions of 1930, 1934 and 1935, Alonzo Church's lambda calculus of 1936, Emil Post's Formulation 1 of 1936, and Alan Turing's Turing machines of 1936–37 and 1939.

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