Who adopts agroforestry in a subsistence economy?—Lessons from the Terai of Nepal
Agroforestry is recognized as a sustainable land use practice. However, the uptake of such a
promising land use practice is slow. Through this research, carried out in a Terai district of …
promising land use practice is slow. Through this research, carried out in a Terai district of …
Data-driven optimization of processes with degrading equipment
In chemical and manufacturing processes, unit failures due to equipment degradation can
lead to process downtime and significant costs. In this context, finding an optimal …
lead to process downtime and significant costs. In this context, finding an optimal …
Prediction of frost occurrences using statistical modeling approaches
H Lee, JA Chun, HH Han, S Kim - Advances in Meteorology, 2016 - Wiley Online Library
We developed the frost prediction models in spring in Korea using logistic regression and
decision tree techniques. Hit Rate (HR), Probability of Detection (POD), and False Alarm …
decision tree techniques. Hit Rate (HR), Probability of Detection (POD), and False Alarm …
Machine learning approach for climate change impact assessment in agricultural production
S Singh, KVS Babu, S Singh - … techniques for climate change with machine …, 2023 - Elsevier
Agricultural production mainly depends on weather conditions. Both aspects are interiorly
connected with each other in several aspects, as climate change is the key factor of plant …
connected with each other in several aspects, as climate change is the key factor of plant …
Maximum entropy derived and generalized under idempotent probability to address Bayes-frequentist uncertainty and model revision uncertainty: An information …
DR Bickel - Fuzzy Sets and Systems, 2023 - Elsevier
Typical statistical methods of data analysis only handle determinate uncertainty, the type of
uncertainty that can be modeled under the Bayesian or confidence theories of inference. An …
uncertainty that can be modeled under the Bayesian or confidence theories of inference. An …
Two-state imprecise Markov chains for statistical modelling of two-state non-Markovian processes
This paper proposes a method for fitting a two-state imprecise Markov chain to time series
data from a two-state non-Markovian process. Such non-Markovian processes are common …
data from a two-state non-Markovian process. Such non-Markovian processes are common …
Recovering forecast distributions of crop composition: method and application to Kentucky agriculture
This paper proposes a novel application of the multinomial logit (MNL) model using
Cropland Data Layer and field-level boundaries to estimate crop transition probabilities …
Cropland Data Layer and field-level boundaries to estimate crop transition probabilities …
Recommending encounters according to the sociodemographic characteristics of patient strata can reduce risks from type 2 diabetes
Objectives Physician encounters with patients with type 2 diabetes act as motivation for self-
management and lifestyle adjustments that are indispensable for diabetes treatment. We …
management and lifestyle adjustments that are indispensable for diabetes treatment. We …
A robust Bayesian analysis of the impact of policy decisions on crop rotations
L Paton, M Troffaes, N Boatman, M Hussein… - 2015 - durham-repository.worktribe.com
We analyse the impact of a policy decision on crop rotations, using the imprecise land use
model that was developed by the authors in earlier work. A specific challenge in crop …
model that was developed by the authors in earlier work. A specific challenge in crop …
Binary credal classification under sparsity constraints
Binary classification is a well known problem in statistics. Besides classical methods, several
techniques such as the naive credal classifier (for categorical data) and imprecise logistic …
techniques such as the naive credal classifier (for categorical data) and imprecise logistic …