Advances in Intelligent and Soft Computing > Soft Methodology and Random Information Systems > Soft Methodology and Probability > 77-84

Advances in Intelligent and Soft Computing > Soft Methodology and Random Information Systems > Soft Methodology and Probability > 85-92

*x*

_{ i }of the measured quantities, we only know the intervals % MathType!MTEF!2!1!+- % feaagaart1ev2aaatCvAUfeBSjuyZL2yd9gzLbvyNv2CaerbuLwBLn % hiov2DGi1BTfMBaeXatLxBI9gBaerbd9wDYLwzYbItLDharqqtubsr % 4rNCHbGeaGqiVu0Je9sqqrpepC0xbbL8F4rqqrFfpeea0xe9Lq-Jc9 % vqaqpepm0xbba9pwe9Q8fs0-yqaqpepae9pg0FirpepeKkFr0xfr-x...

Advances in Intelligent and Soft Computing > Soft Methodology and Random Information Systems > Soft Methodology and Probability > 93-100

Advances in Intelligent and Soft Computing > Soft Methodology and Random Information Systems > Soft Methodology and Probability > 101-108

*Discrete-time stochastic processes on Riesz spaces*, we introduced the concepts of conditional expectations, martingales and stopping times on Dedekind complete Riesz space with weak order units. Here we give a construction of stopping times from sequences in a Riesz space and are consequently able to prove a Riesz space uperossing theorem which is applicable to fuzzy processes.

Advances in Intelligent and Soft Computing > Soft Methodology and Random Information Systems > Soft Methodology and Probability > 109-116

Advances in Intelligent and Soft Computing > Soft Methodology and Random Information Systems > Soft Methodology and Probability > 117-124

*d*

_{ H }

^{∞}, based on the results of set-valued random variable obtained by Taylor and Inoue [34], [35]. This work is...

Advances in Intelligent and Soft Computing > Soft Methodology and Random Information Systems > Soft Methodology and Probability > 125-132

Advances in Intelligent and Soft Computing > Soft Methodology and Random Information Systems > Soft Methodology and Probability > 133-140

Advances in Intelligent and Soft Computing > Soft Methodology and Random Information Systems > Soft Methodology and Probability > 141-148

Advances in Intelligent and Soft Computing > Soft Methodology and Random Information Systems > Soft Methodology and Probability > 149-156

Advances in Intelligent and Soft Computing > Soft Methodology and Random Information Systems > Soft Methodology and Probability > 157-164

Advances in Intelligent and Soft Computing > Soft Methodology and Random Information Systems > Soft Methodology and Probability > 165-172

Advances in Intelligent and Soft Computing > Soft Methodology and Random Information Systems > Soft Methodology and Probability > 173-180

Advances in Intelligent and Soft Computing > Soft Methodology and Random Information Systems > Soft Methodology and Probability > 181-188

Advances in Intelligent and Soft Computing > Soft Methodology and Random Information Systems > Soft Methodology and Probability > 189-196

*A*,

*B*and

*Ø*be mappings from [0, 1]

^{2}into [0, 1], we characterize the properties of

*Ø*which ensure

*Ø*(

*A,B*) is in the same class of A and

*B*. In order to this aim, we introduce the new concept of

*P*-increasing function.

Advances in Intelligent and Soft Computing > Soft Methodology and Random Information Systems > Soft Methodology and Probability > 197-204

*σ*-fields of subsets of the unit interval and idempotent copulas. However, the literature reports few examples of idempotents. Exploiting the correspondence that also exists between idempotent copulas and conditional expectations with respect to the

*σ*-fields just mentioned, we provide a general means of constructing idempotents,...

Advances in Intelligent and Soft Computing > Soft Methodology and Random Information Systems > Soft Methodology and Probability > 205-211

Advances in Intelligent and Soft Computing > Soft Methodology and Random Information Systems > Soft Methodology and Probability > 212-218

Advances in Intelligent and Soft Computing > Soft Methodology and Random Information Systems > Soft Methodology and Probability > 219-226