Quantum Computing for Dealing with Inaccurate Knowledge Related to the Certainty Factors Model

In this paper, we illustrate that inaccurate knowledge can be efficiently implemented in a quantum environment. For this purpose, we analyse the correlation between certainty factors and quantum probability. We first explore the certainty factors approach for inexact reasoning from a classical point of view. Next, we introduce some basic aspects of quantum computing, and we pay special attention to quantum rule-based systems. In this context, a specific use case was built: an inferential network for testing the behaviour of the certainty factors approach in a quantum environment. After the design and execution of the experiments, the corresponding analysis of the obtained results was performed in three different scenarios: (1) inaccuracy in declarative knowledge, or imprecision, (2) inaccuracy in procedural knowledge, or uncertainty, and (3) inaccuracy in both declarative and procedural knowledge. This paper, as stated in the conclusions, is intended to pave the way for future quantum implementations of well-established methods for handling inaccurate knowledge.

Quantum Computing for Dealing with Inaccurate Knowledge using the Certainty Factors Model

In this paper we try to demonstrate that the classical model of certainty factos for dealing with innacurate knowledge can be efficiently implemented in a quantum environment. For this, we assume that certainty factors are strongly correlated with the quantum probability. We first explore the certainty factors approach for inexact reasoning from a classical point of view. Next, we introduce some basic aspects of quantum computing, and we pay special attention to quantum rule-based systems. We then build a use case: an inferential network to be implemented in both, the classical approach and the corresponding quantum circuit. Both implementations have been used to compare the behavior of the classical and the quantum approaches when confronted with the same hypothetical case. We analyze three different situations: (1) Only Imprecision (which refers to inaccuracy in declarative knowledge or facts) is present in the use case, (2) Only Uncertainty (which refers to inaccuracy in procedural knowledge or rules) is present in the use case, and (3) Both Imprecision and Uncertainty are present in the use case. Finally, we analyze the results to reach a conclusion about the eventually intrinsic probabilistic nature of the certainty factors model and to pave the way for future quantum implementations of this method for handling inaccurate knowledge.

Expert System Diagnose Disease in Poultry Using Certainty Factor Method

In this study, the authors conducted research to apply the Certainty Factor Method to Diagnose Diseases in Livestock and build applications in the application of Reviews These methods. Information technology is now a staple in developing a field. Along with the development of the times, proper information management is needed, so we need an Appropriate computational method. In this case the expert system method is one way to find out or identify diseases in poultry that have been infected with bacteria or viruses. A form of management information system specifically created to support a plan in making decisions to solve a case or problem. Artificial Intelligence (Artifical Intelligence) is one part of computer science that makes machines (computers) can do work as and as well as humans do. Expert System is one of the Artificial Intelligence techniques that attempts to adopt human knowledge into computers, so that computers can solve problems as is usually done by experts. Diagnosing disease in poultry is currently a problem that is still underestimated for most people, this is due to lack of knowledge or lack of information in terms of Overcoming and Preventing Contaminated, viruses or bacteria. Certainty Theory Theory was suggested by Shortlife and Buchanan in 1975 to a accommodate the uncertainty of thinking or inexact reasoning of an expert. Phrases like "maybe", "most likely", "almost Certain". To a accommodate this, Researchers conducted a certainty factor method to describe the level of expert confidence in problems in diseases Suffered by chickens already infected with dangerous viruses.

SISTEM PAKAR UNTUK MENDIAGNOSA PENYAKIT LUPUS DENGAN MENGGUNAKAN METODE CERTAINTY FACTOR

Penyakit lupus ialah merupakan suatu jenis penyakit daya tahan organ tubuh, atau penyakit auto imun yang akan menyerang sebagian organ tubuh. Diagnosa awal oleh medis penyakit lupus dapat membantu para pasien berguna mengantisipasi penyakit lainnya yang lebih parah. Suatu Sistem pakar yang akan dapat diterjemahkan berupa sistem berbasis komputerisasi yang akan menggunakan pengetahuan,berbagai fakta, dan teknik cara penalaran dalam memecahkan suatu masalah yang hanya akan dipecahkan oleh seorang pakar ahli dalam bidang itu sendiri.Penggunaan Aplikasi sistem pakar dapat membantu dalam mendiagnosa awal penyakit lupus. Faktor kepastian (Certainty Factor) yang diusulkan oleh Shortliffe dan Buchanan pada tahun 1975 untuk mengakomadasi ketidakpastian pemikiran (inexact reasoning) seorang pakar. Certainty Factor (CF) menunjukkan ukuran kepastian terhadap suatu fakta atau aturan. penerapan metode ini ke dalam sistem pakar diharapkan mampu memberikan solusi praktis untuk mendiagnosa penyakit lupus secara dini.

An improved method of Newmark analysis for mapping hazards of coseismic landslides

Coseismic landslides have been responsible for destroyed buildings and structures, dislocated roads and bridges, cut off of pipelines and lifelines, and tens of thousands of deaths. Newmark's method is widely applied to assess the permanent displacement along a potential slide surface to determine the coseismic responses of the slope. The Mw 6.1 (USGS) earthquake in Ludian, Yunnan Province, China in 2014 has caused widespread landslides and provided the ideal data sets to conduct a regional analysis of coseismic stability of slopes. The data sets include the topography, shear strength, and ground shaking of the study area. All of these data sets are digitized and rasterized at 30 m grid spacing using ArcGIS and combined in a dynamic slope model based on Newmark permanent-deformation analysis. The application of Barton model was then applied in the permanent-deformation analysis. According to a method of inexact reasoning, comparisons are made between the predicted displacements and a comprehensive inventory of landslides triggered by the Ludian earthquake to map the spatial variability in certainty factors. A coseismic landslide hazard map is then produced based on the spatial distribution of the values of certainty factors. Such map can be applied to predict the hazard zone of the region and provide guidelines for making decisions regarding infrastructure development and post-earthquake reconstruction.

Research on Cow Epidemic Disease Diagnosis Based Certainty Factor

According to actual of cow epidemic disease diagnosis, bidirectional reasoning scheme based on the symptom both characterization and autopsy is proposed, which is based on inexact reasoning of certainty factor. The process of both construction the knowledge database for cow epidemic disease diagnosis and the inexact reasoning based on certainty factor are amplified. A web-based system on the platform of Tomcat+JSP+MySQL+DWR about the cow epidemic disease diagnosis is realized base on MVC. By testing, it is shown that the monitoring 21 kinds of cow epidemic disease in China can be accurately diagnosed, basically. It can be widely used in breeding aquatics village, breeding farm, raising households and so on. It will play a positive role to prevent and control the cow epidemic disease.