Errors and residualsIn statistics and optimization, errors and residuals are two closely related and easily confused measures of the deviation of an observed value of an element of a statistical sample from its "true value" (not necessarily observable). The error of an observation is the deviation of the observed value from the true value of a quantity of interest (for example, a population mean). The residual is the difference between the observed value and the estimated value of the quantity of interest (for example, a sample mean).
Lithium–air batteryThe lithium–air battery (Li–air) is a metal–air electrochemical cell or battery chemistry that uses oxidation of lithium at the anode and reduction of oxygen at the cathode to induce a current flow. Pairing lithium and ambient oxygen can theoretically lead to electrochemical cells with the highest possible specific energy. Indeed, the theoretical specific energy of a non-aqueous Li–air battery, in the charged state with Li2O2 product and excluding the oxygen mass, is ~40.1 MJ/kg = 11.14 kWh/kg of lithium.
Root-mean-square deviationThe root-mean-square deviation (RMSD) or root-mean-square error (RMSE) is a frequently used measure of the differences between values (sample or population values) predicted by a model or an estimator and the values observed. The RMSD represents the square root of the second sample moment of the differences between predicted values and observed values or the quadratic mean of these differences. These deviations are called residuals when the calculations are performed over the data sample that was used for estimation and are called errors (or prediction errors) when computed out-of-sample.
Lithium–sulfur batteryThe lithium–sulfur battery (Li–S battery) is a type of rechargeable battery. It is notable for its high specific energy. The low atomic weight of lithium and moderate atomic weight of sulfur means that Li–S batteries are relatively light (about the density of water). They were used on the longest and highest-altitude unmanned solar-powered aeroplane flight (at the time) by Zephyr 6 in August 2008. Lithium–sulfur batteries may displace lithium-ion cells because of their higher energy density and reduced cost.
Mean squared prediction errorIn statistics the mean squared prediction error (MSPE), also known as mean squared error of the predictions, of a smoothing, curve fitting, or regression procedure is the expected value of the squared prediction errors (PE), the square difference between the fitted values implied by the predictive function and the values of the (unobservable) true value g. It is an inverse measure of the explanatory power of and can be used in the process of cross-validation of an estimated model.
Electric batteryA battery is a source of electric power consisting of one or more electrochemical cells with external connections for powering electrical devices. When a battery is supplying power, its positive terminal is the cathode and its negative terminal is the anode. The terminal marked negative is the source of electrons that will flow through an external electric circuit to the positive terminal. When a battery is connected to an external electric load, a redox reaction converts high-energy reactants to lower-energy products, and the free-energy difference is delivered to the external circuit as electrical energy.
Lithium metal batteryLithium metal batteries are primary batteries that have metallic lithium as an anode. These types of batteries are also referred to as lithium-metal batteries after lithium-ion batteries had been invented. Most lithium metal batteries are non-rechargeable. However, rechargeable lithium metal batteries are also under development. Since 2007, Dangerous Goods Regulations differentiate between lithium metal batteries (UN 3090) and lithium-ion batteries (UN 3480). They stand apart from other batteries in their high charge density and high cost per unit.
Residual sum of squaresIn statistics, the residual sum of squares (RSS), also known as the sum of squared residuals (SSR) or the sum of squared estimate of errors (SSE), is the sum of the squares of residuals (deviations predicted from actual empirical values of data). It is a measure of the discrepancy between the data and an estimation model, such as a linear regression. A small RSS indicates a tight fit of the model to the data. It is used as an optimality criterion in parameter selection and model selection.
Regularization (mathematics)In mathematics, statistics, finance, computer science, particularly in machine learning and inverse problems, regularization is a process that changes the result answer to be "simpler". It is often used to obtain results for ill-posed problems or to prevent overfitting. Although regularization procedures can be divided in many ways, the following delineation is particularly helpful: Explicit regularization is regularization whenever one explicitly adds a term to the optimization problem.
SupercapacitorA supercapacitor (SC), also called an ultracapacitor, is a high-capacity capacitor, with a capacitance value much higher than other capacitors but with lower voltage limits. It bridges the gap between electrolytic capacitors and rechargeable batteries. It typically stores 10 to 100 times more energy per unit volume or mass than electrolytic capacitors, can accept and deliver charge much faster than batteries, and tolerates many more charge and discharge cycles than rechargeable batteries.
