objective function
A New Objective Function for Word Alignment
... We extend our objective function straightfor- wardly to sub-word alignment. To test our exten- sion, we construct a Turkish-English corpus of 1616 sentence pairs. We first manually construct a regu- lar ...
8
A New Load-Balancing Aware Objective Function for RPL’s IoT Networks
... In this study, a new load balancing Objective Function called LBSR is proposed for the RPL protocol. In particular, a new routing primitive is devised to calculate number of children. In addition, a parent ...
7
Cluster Interfaced Objective Function for Decision Tree Classifiers for Mining Data with Uncertainty
... We've given the execution time of Cluster Interfaced purpose characteristic. be aware that Cluster Interfaced purpose characteristic assembles diverse preference timber via Distance limit bunching system and intention ...
6
New Mathematical Approach for Economic Power Dispatch Problem with Quadratic Objective Function
... A new method based on superlinear bracketing approach is proposed to find the solution of quadratic objective function with equality and inequality constraints. The lambda value of lagragian multiplier ...
5
Adoptive Trend Following Strategy In Financial Time Series With Multi-Objective Function
... Abstract: Given the complex nature of the stock market, determining the stock market timing - when to buy or sell is a challenge for investors. There are two basic methodologies used for prediction in financial time ...
10
Efficient Optimization of an MDL Inspired Objective Function for Unsupervised Part Of Speech Tagging
... the number of non-zero parameters in θ. The hyperparameter α controls the tradeo ff between likelihood maximization and model minimization. Note the similarity of this objective function with MDL’s, where α ...
6
, where C0 is the current objective function coefficient and the fun here presents the perturbation vector. The parametric programming on objective function coefficient will observe the behavior of solution with respect to the change of III. SIMPLEX BASED
... parametric objective coefficient programming, the parameter interval is determined by ensuring the reduced cost still satisfy the optimal condition, so that the current basis will stay optimal in the whole ...
5
Information Theory Interpretation of the Skip Gram Negative Sampling Objective Function
... energy function takes the form of a dot product between the vectors of an observed word and an observed ...tive function is a binary logistic regression classifier that treats a word and its observed ...
5
Separated Continuous Linear Programs with Fuzzy Valued Objective Function
... Abstract. Fuzzy linear programming problems can be used to model a wide variety of practical applications in which all or some decision parameters are stated in an imprecise fashion. These problems have been investigated ...
14
Minimum Energy Consumption Objective Function For RPL In Internet Of Things
... Thus the comparison between two objective function was done using Cooja simulator. The performance was measured between the of0 and mrhof objective function by varying number of branches and ...
8
Union Membership and Employment Dynamics: The Role of the Union Objective Function
... DOI: 10.4236/tel.2019.95094 1478 Theoretical Economics Letters a static model, in which maximising the wage bill leads to the same level of em- ployment as maximising the wage surplus, the union objective ...
7
Optimal Location and Capacity of Distributed Generation for Multi-objective Function using Bat Algorithm
... multi-objective function [5] ...multi- objective function to find optimal position and capacity of DGs like Genetic Algorithm [7], Particle Swarm Optimization (PSO) [8], ant colony [9], ...
8
Question 2: How will changes in the objective function s coefficients change the optimal solution?
... increased to a value greater than 120, (15, 20) is no longer part of the optimal solution. As long as the coefficient on x in the objective function falls between 40 to 120, the optimal solution includes ...
6
Empirical Formulation of Highway Traffic Flow Prediction Objective Function Based on Network Topology
... A shallow LSTM-NN architecture is effective in capturing the spatio-temporal dependencies on node level with defined topological link order and this can be extended to further inter connected nodes and links. Thus, in ...
13
A simpler method to solve Optimal Power Flow problem with non differentiable objective function
... quadratic objective function [10].The DMcan not solve the OPF problem with non-differentiable objective function. The Particle Swarm method [11]-[17]is not accurate because it has a ...
10
Objective function design for robust optimality of linear control under state-constraints and uncertainty
... Abstract . We consider a model for the control of a linear network flow system with unknown but bounded demand and politopic bounds on controlled flows. We are interested in the problem of finding a suitable ...
23
Revisiting LSTM Networks for Semi-Supervised Text Classification via Mixed Objective Function
... In this paper, we study bidirectional LSTM network for the task of text classification using both supervised and semi- supervised approaches. Several prior works have suggested that either complex pretraining schemes ...
9
Objective Function Learning to Match Human Judgements for Optimization Based Summarization
... the objective function by making simplistic assumptions to ensure conve- nient mathematical properties of θ like linearity or submodularity (Lin and Bilmes, ...
7
A Diversity Promoting Objective Function for Neural Conversation Models
... tion. These models tend to generate safe, common- place responses (e.g., I don’t know) regardless of the input. Our analysis suggests that the issue is at least in part attributable to the use of unidirectional like- ...
10
Firefly algorithm for economic emission dispatch with normalized objective function
... The economic emission dispatch (EED) assumes a lot of significance to meet the clean energy requirements of the society and simultaneously minimizes the cost of generation. The Firefly Algorithm (FA) is a nature-inspired ...
5