This work presents a hybrid model of Case-based Reasoning (CBR) and artificial immune
systems (AIS), which is able to manage the processes of recovery, adaptation (reuse and …

In machine learning area, a large number of classification algorithms are available that can
be used for solving the problems of prediction and classification in different domains. These …

A tight integration between model-based approach and Case-Based Reasoning (CBR) as
data-driven AI technology for advanced process control of periodical industrial plants …

Case-based Reasoning (CBR) has been widely applied in the medical expert systems. CBR
has computational time constraints if there are too many old cases on the case base. Cluster …

In practical data mining, a wide range of classification algorithms is employed for prediction
tasks. However, selecting the best algorithm poses a challenging task for machine learning …

Ethiopia, having the majority of its population living in rural areas and agriculture being the
backbone of its economy, is one of the African countries with bigger cattle population …

Case-based Reasoning (CBR) is a problem solving approach applied to different cognitive
systems for planning, decision making, etc. This approach benefits/utilizes the solutions of …

Situation recognition is a process used to support actions and forthcoming predictions for
actual situation as well as decision making in cognitive systems. This process may improve …

Ontology is commonly defined as a formal specification of knowledge conceptualization in a
consensual form. OWL (Web Ontology Language) is the most used and expressive ontology …

This study aims to improve the performance of Case-Based Reasoning by utilizing cluster
analysis which is used as an indexing method to speed up case retrieval in CBR. The …