Land use exceeds the standard of suitability and availability over Indonesia, which causes uncontrolled land acquisitions every year. Changes in can be controlled by monitoring changes cover effect on hydrological cycle components such as cloud fraction. The fraction distribution were identified using NDVI index parameters. value Indonesia is 0.73 to 0.81, representing relatively high. Meanwhil...

In this paper we present a new probability function G that generalizes the classical probability function. A mass function is an assignment of basic probability to some context (events, propositions). It represents the strength of support for some contexts in a domain. A context is a subset of the basic elements of interest in a domain – the frame of discernment. It is a medium to carry the “pr...

Uncertainty in production prediction has been subject to numerous investigations. Geological and reservoir engineering data comprise a huge number of data entries to the simulation models. Thus, uncertainty of these data can largely affect the reliability of the simulation model. Due to these reasons, it is worthy to present the desired quantity with a probability distribution instead of a sing...

Stochastic programming is a valuable optimization tool where used when some or all of the design parameters of an optimization problem are defined by stochastic variables rather than by deterministic quantities. Depending on the nature of equations involved in the problem, a stochastic optimization problem is called a stochastic linear or nonlinear programming problem. In this paper,a stochasti...

The α-μ distribution is a generalized fading distribution which explores nonlinearities of the wireless propagation medium. This distribution includes the other distributions such as Gamma, Nakagami, exponential, Gaussian, Rayleigh etc. This makes α-μ distribution very interesting. In this paper probability density function and performance metrics such as outage and bit error rate of α-μ distri...

1 Probability distribution functions Probability distribution functions assign probabilities to each of the possible outcomes of a random experiment. These distributions can be continuous (e.g. grading on a 4.0 scale), or discrete (e.g. grading with letter grades) (see Fig. ??). Figure 1: Terminology for continuous and discrete probability distributions. A probability distribution function spec...

1 Probability distribution functions Probability distribution functions assign probabilities to each of the possible outcomes of a random experiment. These distributions can be continuous (e.g. grading on a 4.0 scale), or discrete (e.g. grading with letter grades) (see Fig. 2). Figure 1: Terminology for continuous and discrete probability distributions. A probability distribution function speci...

1 Probability distribution functions Probability distribution functions assign probabilities to each of the possible outcomes of a random experiment. These distributions can be continuous (e.g. grading on a 4.0 scale), or discrete (e.g. grading with letter grades) (see Fig. 2). Figure 1: Terminology for continuous and discrete probability distributions. A probability distribution function speci...