Build a positive impact. Our offered research topics
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Data analytics refers to qualitative and quantitative techniques and processes used to enhance productivity and business gain. Data is extracted and categorized to identify and analyze behavioral data and patterns, and techniques vary according to organizational requirements.
Data analytics is also known as data analysis.
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Machine learning is a method of various type data, images and signals analysis being used in a wide range of applications today. Machine learning platforms are being practiced among enterprise technologies as such by Amazon, Google, Microsoft, IBM in machine learning activities to support their business processes. It is becoming demanding now in assisting big data solutions with modern machine learning of a better performance in detection, recognition, classification and clustering of structured and unstructured data. We have the capability of providing these solutions to your organizations
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Knowledge-based systems (KBS) are one of the branches of artificial intelligence. (AI). KBS uses knowledge from human domain experts to facilitate the decision-making process. An example of KBS is expert systems. Among the methods used to reason a decision-making process in KBS are fuzzy logic, rule-based and case-based reasoning. The main components of KBS include user interface facilities, inference engine, and knowledge base. The application of KBS varies from legal, business, medical and other relevant domains.
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Computing Optimization Solution solves difficult optimization problems. Optimization problems concern on the importance of searching for a better solution in many disciplines. It seeks to find the best answer from all possible solutions with the aim of the aim is to maximize or minimize the objective functions such as to maximize productivity and maximized security and minimized operating costs. Some of the optimization problems are scheduling and planning, routing, assignment, space, resources in various industries and organizations. Many natures inspired computing solutions we employed and improved to suit customer needs.
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A simulation model is a set of interacting objects that represent the actual relationships in the real world. In the case of agent-based simulation, autonomous agents interact and make decisions to simulate the real world. Examples of agent-based applications are widely used in the social sciences and business domain. The agent-based application supports autonomous decision-making in distributed systems. Examples of agent-based architecture are used in robotics, personal agents and autonomous cars.
