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Jan M. Maciejowski is a British electrical engineer. He is professor emeritus of control engineering at the University of Cambridge . He is notable for his contributions to system identification and control .
Model predictive control (MPC) is an advanced method of process control that is used to control a process while satisfying a set of constraints. It has been in use in the process industries in chemical plants and oil refineries since the 1980s.
Uplift modelling uses a randomised scientific control not only to measure the effectiveness of an action but also to build a predictive model that predicts the incremental response to the action. The response could be a binary variable (for example, a website visit) [ 1 ] or a continuous variable (for example, customer revenue). [ 2 ]
Depending on the configuration, open-chain robotic manipulators require a degree of trajectory optimization. For instance, a robotic arm with 7 joints and 7 links (7-DOF) is a redundant system where one cartesian position of an end-effector can correspond to an infinite number of joint angle positions, thus this redundancy can be used to optimize a trajectory to, for example, avoid any ...
Marketing mix modeling (MMM) is an analytical approach that uses historic information to quantify impact of marketing activities on sales. Example information that can be used are syndicated point-of-sale data (aggregated collection of product retail sales activity across a chosen set of parameters, like category of product or geographic market) and companies’ internal data.
Bayesian decision analysis can also be applied to the channel selection process. In order to help provide further information the method can be used that produces results in a profit or loss aspect. Prior information can include costs, expected profit, training expenses and any other costs relevant to the decision as well as managerial ...
Conjoint analysis is a survey-based statistical technique used in market research that helps determine how people value different attributes (feature, function, benefits) that make up an individual product or service. The objective of conjoint analysis is to determine the influence of a set of attributes on respondent choice or decision making.
Predictive modelling uses statistics to predict outcomes. [1] Most often the event one wants to predict is in the future, but predictive modelling can be applied to any type of unknown event, regardless of when it occurred. For example, predictive models are often used to detect crimes and identify suspects, after the crime has taken place. [2]