Discover @mendaxyazilim Open Source projects

MENDAX (@mendaxyazilim)

mendaxyazilim

Stars
31
Global Rank 479,903 (Top 17 %)
Followers 11
Registered about 7 years ago
Most used languages

Python
45.5 %

Processing 27.3 %

JavaScript
18.2 %

Shell
9.1 %
Location 🇹🇷 Turkey
Country Total Rank 2,689
Country Ranking

Processing 4

Shell
173

Python
1,111

JavaScript
3,336

mendaxdroid

MendaxDroid is a framework that create & generate & embed apk payload to penetrate androids

apt29

apt28

A powerful flooding tool

mxroc

Rocket Design and Test Simulator

apt30

Backdoor and Listener

chessus

Chessus Yapay Zeka Satranç Oyunu - Kendini satrançta geliştirmek için genetik algoritma kullanan bir sinir ağ sistemidir.

project-adam

Producing long pieces of music is a difficult task, as music includes structures in many time periods, from millisecond timings to motifs and notes. We offer you Music Transformer Adam Ive, which can produce music with long-term consistency.

ERL-Cellular-Automata-Model

In this study, we examine cell regeneration with cellular automata. Cellular automata was first introduced by Von Neumann, who determined the working principles of today's computer architecture to model the self-renewal capabilities of biological entities. Cellular automata includes a computational model based on state update logic due to interaction with cells around cells in the grid plane. Studies on cellular automata have shown that some situations interact dynamically with other states. Morphogenesis is the process of forming the shape of an organism and Morphogenesis is one of the most striking examples of a phenomenon called self-organization. We are trying to replicate some of the desired features with this artificial intelligence model that we have made, to help solve the morphogenetic code puzzle and also take advantage of biology's insights to create real-life self-healing systems.

ghb-language-acquisition-model

I will introduce the GHB language acquisition model. In this project, we were able to create text predictions and text. Learning capacity of our GHB language acquisition model (1.5 billion); AI2 (465 million) is well above the learning capacity of Facebook Ai (355 million) and Google Ai (340 million). You can check our website for the rest of the article. GHB dil edinim modelini tanıtacağım. Bu projede, metin tahminleri ve metin oluşturmayı başardık. GHB dil edinme modelimizin öğrenme kapasitesi (1,5 milyar); AI2 (465 milyon), Facebook Ai (355 milyon) ve Google Ai’ın (340 milyon) öğrenme kapasitesinden oldukça yukarıda. Yazının devamı için web sitemize gidebilirsiniz.

mendaxcloud

Mendax CloudFlare Bypasser

yilanoyunu

Yapay zeka sinir ağ ile yılan oyunu oynamayı öğreniyor.

dos

DoS ve Racon Saldırılarını Kolay Hale Getiriren Linux Toolu.

mendaxwp

MendaxWp, tüm penetrasyon testlerini bir araya getirmiş yazılımdır. MendaxWp, farklı görevler yerine getirmek için farklı araçlar başlatmak yerine, Penetrasyon Testleri ve Güvenlik Araştırmacılarının işlerini kolaylaştırmak için özel olarak programlanmıştır. MendaxWp, hedef websitenin bilgileri toplayan ve içinde ki açıkları tarayan birçok özellik sunar.

akilli-noktalar

Noktaların hedefe ulaşması için bir simülasyon yapılır. Simülasyonun sonundaki Genetik Algoritma, önceki neslin en iyi noktalarından yeni bir nesil nokta üretimi gerçekleştirir. Noktalar hedeften uzaklığı, ulaşmak için attığı adımların sayısı, vb. gibi faktörlere göre kendi içerisinde derecelendirilir. Noktalar hedefe ulaşmaya çalışır. Bir süre sonra kuşaklarda iyi mutasyonlar yayılır ve genel zindelik artar. Yeterince uzun süre verildiğinde algoritma hedefe en kısa yoldan ulaşır.

chessusv2

Ever since the advent of Artificial Intelligence (AI), game playing has been one of the most interesting applications of AI. The first chess programs were written by Claude Shannon and by Alan Turing in 1950, almost as soon as the computers became programmable. Games are very appealing and writing gameplaying programs is perhaps even more exciting. Unlike other chess engines, we do not allow algorithms to focus on beating the opponent. With the help of the algorithms we use (minimax and alpha-beta pruning), we have developed a chess engine that tries to find the worst situation and get rid of it. We should not expect game playing algorithms to be perfect for every situation. Remember the main purpose of the algorithm before play. The aim of the algorithm is not to beat the opponent but to get rid of the worst situation.

facetracker